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Segmentation of investors based on saving motives.


Saving motive is a desire to reserve certain portion of income for future needs. Noted economist Keynes has given eight factors which were believed to lead individuals to abstain from spending out of their incomes. The saving rate of household is affected not only by their ability to save but also by their willingness to save. India could be able to save 32 percent of its Gross Domestic Product irrespective o fits low per capita income and high inflation rate mainly because of the attitude of people to save. This study attempts to find out the level of saving motive of Indian salaried class people. The next objective is to segment the investors based on their level of motives. This will be useful to the marketers of investment products to concentrate more on specific segment where people have high level of motivation to save because convincing them to make investment on their products will be easy.

Keywords: Saving motives, Segmentation of investor using saving motives, Characteristics of investor, Testing suitability of investor segmentation

JEL Classification: D14, E21


Financing socio-economic activities in a country requires large amount of resources, which is not possible to secure from taxation alone. It can be carried only through a rise in the rate of capital formation. In the opinion of L.G. Whyte (1976) the future welfare of any country depends, to a great extent upon a high level of investment on capital goods. This is possible only by the generation of an adequate volume of savings. Developing economies lay great emphasis on the importance of domestic savings as they are the source of investment to break the vicious circle of poverty and under employment. Arthur Lewis (1963) asserts that the obstacle to greater investment in the less developed countries is that their current propensity to save is too low.

It has been estimated that the rate of saving in the initial stages of growth of present day advanced economies remained nearly 20 percent of their national income. A study on the pattern of savings in Japan during the post war period revealed that the exceptionally high rate of capital formation in Japan resulted from consistent rate of saving of over 20 percent throughout the period, and with such a high rate of savings, Japan could easily surpass even some of the highly industrialized economies of the west (Sinha, 1964). In a study (Andrea Poltho, 1975) it has been shown that Japan invested 31.8 percent of its GNP (at constant prices) between 1953 and 1972 and during the same period, it was 25.1 percent for West Germany, 23 percent for France, 20.2 per cent for Italy, 17.3 per cent for UK and 17.0 per cent for USA.

The volume of aggregate saving is made up of private savings by individuals or business, savings by the companies, and public savings by the government. This composition may vary from country to country and time to time in the same country. In the democratic welfare states like the United Kingdom, Sweden and France, contribution of corporate and government savings to the total savings is more than 60 percent, whereas in India, Canada and Japan individuals' saving is more, especially in India it is more than 80 percent. This indicates that the higher percentage of corporate savings is due to high industrialization. The reason for less government savings in welfare states like India is that they have invested a large amount on social services and social well being by borrowing on a large scale. People as individuals need to save not only to meet emergencies and uncertainties in future but also to maintain their status in the society.

Many research works have been carried out to find out the variables which could affect the savings rate of the households. The variables identified by the previous researchers are economic variables, psychological variables, social variables and behavioural variables. To put it in simple term the saving is the product of ability to save and willingness to save. The ability to save is influenced by income and wealth of individual. The willingness to save is determined by saving motives. In the absence of other factors the individual saving is the function of their saving motives. Hence it can be presumed that the highly motivated people will save more than the least motivated people. As the motivation level of highly motivated people is high, convincing them to make investment will not require much effort. To sell more with limited effort, the institutions who offer investment products can concentrate on highly motivated segment. To device effective marketing strategy, it is necessary for them to understand the characteristics of this motive segment. Therefore it is necessary to segment the investor into highly motivated and least motivated based on the level of motive. The present study aims to serve that purpose.


While it is common to associate interest in motives with psychologists, economists have long been interested in knowing the motives for saving. For example, Adam smith (1776/ 1993) speculated that "the principle which prompts us to save is the desire of bettering our condition, a desire which is generally calm and dispassionate, comes with us from the womb, and never leaves us still we go into the grave". John Maynard Keynes (1936) proposed eight saving motives: the precautionary, life cycle, intertemporal substitution, improvement, independence, enterprise, bequest, and avarice i.e., inhibitions against acts of expenditure as such. More recently, neo-classical economists have emphasized four motives for saving, including the desire: (1) to maintain consumption in the face of income fluctuations, particularly during retirement; (2) to prepare for income shocks and other emergencies (precautionary saving); (3) to transfer wealth to future generations (bequest motive); and (4) to purchase big ticket items such as consumer durables, education, or a vacation (target saving). The first three are expected to influence long term saving, and the fourth to affect short to medium term saving and dissaving patterns (Sturm, 1983). At the same time, as Owens (1993) says, "these motives are not mutually exclusive, and saving decisions will generally be influenced by more than one of them". Empirical studies observe that Americans generally cite retirement, emergencies, and education as the primary motives for saving (Avery et al., 1986; Bernheim, 1994; Modigliani, 1988; Sturm, 1983). However, it is quite possible that the silence of particular motives varies by socioeconomic status (Solmon, 1975; Avery et al., 1986).

Several of these motives were developed into formal economic models (Browning & Lusardi, 1996). The most influential saving model is the life cycle models (Ando & Modigliani, 1963). This model states that current consumption spending depends on current wealth and lifetime income so that consumers borrow and save to smooth out their consumption throughout their life cycle. This model thus implies a saving motive for retirement. This model was further revised to include intergenerational transfer motive (saving for children) (Barro, 1978; Kurz, 1984) and precautionary motive (Saving for emergencies) (carroll, 1997). Empirical studies using U.S. data were conducted to investigate saving behaviour associated with saving motives for emergencies and retirement (Johnson & Widdows, 1985; Yuh, Montalto, & Hanna, 1998). Using U.S. macro data, Feldtein (1974, 1996) found that social security reduces private savings, indicating that social institutions affect private saving motives. Many economists have noted the limitations of the life cycle model. For example, Wolff (1981) divided families into three classes: the capitalist, the primary working class, and the secondary work force. He found that only the primary working class takes the form of life cycle wealth. Katona (1960, 1980) stressed the importance of psychological aspects of people's economic behaviour and empirically studied saving motives and behaviour using survey methods, which were earlier versions of the Survey of Consumer Finances. His study showed that people's new saving motives emerge when the old saving needs is met and the income is positively related to the number of saving motives (Katona, 1960). Kennickell, Starr-McCluer, & Surette, (2000) using the 1998 survey of consumer Finances data shows that the proportion of families reporting education related reasons for saving has risen since 1989. The Indian households save mainly for the purpose of meeting future contingencies (NCAER, 1964) and for the purpose of meeting the needs of their children (Somasundaram, 2004). From the past studies it is clear that motives of saving are changing over a period of time. So far no study has been conducted to find out the characteristics of people with different levels of motivation.


The primary data have been collected by conducting a survey among teachers working in Government colleges and Universities in Tamil Nadu using well structured questionnaire. The population size was 11867 and the sample size of 614 was calculated by using formula n = [Z.sup.2] *p * q * N/[e.sup.2]* (N-l) + [Z.sup.2] *p *q (Kothari.C.R., 2005) where n is the minimum sample size required. The 614 sample respondents were selected by using multi stage random sampling. The questionnaires were distributed to all 614 selected respondents in person by the researcher. After careful and repeated persuasion only 586 filled questionnaires were received and the remaining respondents did not respond. 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 percent. The margin of error for the present sample size of 552 is 1.454 percent. The content validity of the questionnaire was verified by panel of experts from the fields of statistics, psychology, management, commerce and investment consultancy. The criterion validity and construct validity have been tested using correlation analysis. The reliability of the survey instrument was tested using Cronbach Alpha method. The standardized item alpha was 0.6879 and the Hotelling's T-square was 909.2650 and probability was 0.0000. This shows that these statements are reliable and will produce desired result consistently.


Saving was treated as residual unspent income (Lunt & Livingstone, 1991). Consistent with this view, Keynes described eight factors which were believed to lead individuals to refrain from spending out of their incomes. Furnham (1985) summarized these findings as follows

(1) Precaution: Desire to build reserve for unforeseen contingencies.

(2) Foresight: To provide for anticipated future needs like old age.

(3) Calculation: Desire to enjoy an enlarged future income like interest and appreciation.

(4) Improvement: To meet gradually increasing expenditure in order to improve the standard of living.

(5) Independence: To enjoy a sense of independence and power to do things.

(6) Enterprise: Desire to carry out speculation business.

(7) Pride: to pass the fortune to next generation (bequeath a fortune).

(8) Avarice: To spend less (satisfy a purely miserly instinct).

Keynes has given not only motives for saving but also offered a list of motives for consumption which include enjoyment, shortsightedness, generosity, miscalculation, ostentation and extravagance.


The investors were asked to rate their motives level in five points Likert rating scale. The value 1 is assigned for very strongly disagree and 5 is assigned for strongly Agree. The mean value of importance assigned to every motive by the investors is given in the table 1.

The investors give more importance to precautionary motive which means that people want to build reserve to meet unforeseen contingencies. The Indian investors have not shown much interest for the speculative motive which is otherwise called enterprise motive. In the order of priority people want to save money mainly for precautionary motive and least priority is given to speculative motive. The mean values of two motives namely Enterprise and Avarice are less than three which indicate that most of the people do not agree with the existence of such motives for the purpose of saving. The mean values of all other six motives are more than three which explains the existence of such motives for saving. As the motive has influence on saving and the presence of strong motive for saving among Indians makes them save more though their per capita income is less when compared to developed countries.


To reduce the number of variables into minimum manageable variables, factor analysis is performed. The suitability for factor analysis is tested using two analysis 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 won't be very useful.

Table 2 shows that the KMO value as 0.731 which indicates that the factor analysis is useful with the data. The chi-square value for Bartlett's test of Sphericity is 804.442 and the significant value is 0.000 which is significant at more than 99 percent level of confidence. For the purpose of extraction, Principal Component Analysis is used and for the rotation Varimax rotation is used which is the standard rotation method (Kaiser,1958). The factors which have Eigen value greater than unity are taken as reduced factors which are used as new factors for further analysis. From the factor analysis two factors are extracted from original eight variables. Five variables (motives) are grouped under the first factor and another three variables are included in the second factor. The first factor can be named as self support motive and the second factor can be designated as family oriented motive. The motives which are included in the each factor along with their loadings are given below.

(i) Self Support Motive

Self support motive is a motive related to needs and wants of an individual. People mainly want to reserve some money for the purpose of meeting their own future contingencies. The variables included under this motive along with their respective loadings are given in the Table 3.

The need to save for future anticipated requirements and the need to save for future unexpected contingencies are the primary motives included under self support motive. People also save to live independently and to have higher standard of living.

(ii) Family Oriented Motive

People not only reserve money for the purpose of meeting their own needs and they also give equal importance to family related needs. They want to leave some assets to their family members after their death. For the purpose of creating more assets to their family members, they may spend less during their life time and may involve into some business to earn more money.

From the above analysis, the eight motives of saving given by Keynes are reduced into two factors namely self support motive and family oriented motive. For the purpose of future analysis only these two motives are considered.


The following table shows mean value for the self support motive and family oriented motive which signifies the importance of each motive.

Of those two motives self support motive is very dominant than family oriented motive and its presence is very strong among individual investors. The average level of self support motive among individuals is 3.54 which indicates that its presence is very predominant among individuals.

About 95 percent of people agree with the need to save to support them in future. The self support need mainly comprises of the need to save for meeting future unforeseen contingencies and future anticipated expenses. The presence of strong motives among Indians indicates that people will definitely save if they have any surplus money after meeting their basic consumption needs.

Of the total investors only 52 percent of investors agree with the need to reserve money for family oriented needs. The family oriented need is represented by need to create assets to leave it for their future family use. The presence of family oriented motives among investors is much less than self support motives.


The Eigen value and variance explained by each factor (motive) is given in the table 8.

The reduced two factors explain 52.5 percent of total variance which is fairly significant. Among the two motives, self support occupies pivotal position and it alone explains 29.3 percent of total variance. This indicates that the primary motive of every individual is self support motive and individuals differ from each other mainly on the level of their self support motive.


The individual investors can be grouped on the basis of similarities between these two factors namely self support motive and family oriented motive. Cluster analysis is performed for the purpose of segmentation of investors based on the level of motives they have on self support motive and family oriented motive.

If the investors are grouped into three segments then the first group can be called as highly motivated group because their average level of motivation is high when compared to the other two groups and they can also be called as family oriented group because they rank first in the family oriented motive. The second group can be called as least motivated group because they are not agreeable to the existence of both self support motive and family oriented motive. The third group can be christened as average level motivated group because their average level of motivation is around three which is in the middle of 1 to 5 point scale. The third group can also be called as self centered group because they have very strong self support motive.

The Analysis of variance explains that both motives are playing influential role in dividing the investors into three groups. The Anova table also indicates that there exists a significant difference in the mean scores of these three groups on both self support motive and family oriented motive. The significant difference in mean score indicates that these three groups can be explained by using these two motive categories.


A brief description of the three motive based investor groups namely highly motivated, least motivated and self centered segments is given below.

(i) Highly Motivated Investors

The motivation level of this group is high in both the family oriented motive and self support motive as the mean values of both motives are above three in the five point rating scale. They rank among the top in the family oriented motive, second in the self support motive and first in the over all average of mean values of both motives. Though they are second in the self support motive they can be termed as highly motivated group because their motivational level is high in both motives. In the sample of 552 respondents 206 respondents are in this group which means that 37 percent of investors are highly motivated.

(ii) Least Motivated Investors

The second segment of people with respect to motives of savings is called Least Motivated Investors because people in this segment have least level of motivation for savings. This group has very less level of motivation on family oriented motives and self support motives and the mean values of both these motives are less than three in the five point scale. They also rank third in both motives. They also have less level of motivation for saving in the over all average of mean values. In the overall investor population, around 25% of investors are in this category.

(iii) Self Centered Investors

The average score of mean values of both motives of this segment is 3.01; hence this group can be treated as average motivation groups. This group can also be treated as self support motivated group because they have very high level of self support motive. As these groups have high level of self support motive, very least and insignificant level of family oriented motive, this group of investors can be called as self centered investors. Around 38 percent of investing population is in this category.

Table 12 explains the number of people present in each cluster. The highly motivated group and the self centered group account for 75 percent of the total population.

If the investors are grouped into two clusters then 45% of the investors are highly motivated investors and 55% of the investors are least motivated investors. The self centered people are mainly grouped into least motivated group because they have insignificant level of motivation in family oriented motives.


The investors are classified into three clusters based on the level of motives they have for savings. The three identified clusters are highly motivated clusters, self centered clusters and least motivated clusters. Around 37 percent of investors are treated as highly motivated people and 25 percent of investors are least motivated people and 38 percent of the investors are self centered people. The next primary question is whether the identified clusters are genuine and each cluster differs from the other significantly and both motives play a role in separating investors into three segments. For this purpose discriminant analysis is used.

Wilks' lambda is the ratio of the within-groups sum of squares to the total sum of squares. Wilks' lambda is very small for family orientation which means there is a strong group difference among the three motive segmentation in a family oriented motive. The mean values of family oriented motive are significantly different among the three segments. Wilks' Lambda for self support motive is comparatively high because there is no much difference between the first segment and the third segment in the mean values of self support motive. The F statistic is a ratio of 'between-groups variability' to the 'within-groups variability'. The value of F ratio with respect to degrees of freedom is very significant which is indicated in the significance value. The low value of significance indicates that there exists a significant difference in motivational levels among the three groups. The above two facts explain that the present segmentation is right and there exists a significant group difference.

The Eigen value is the ratio of 'between-groups sum of squares' and 'within-groups sum of squares'. The largest Eigen value corresponds to the maximum spread of the groups' means. Small Eigen accounts for very little of the total dispersion. The Eigen for first discriminant function is very high when compared to second function. For the three clusters two discriminant functions can be formed and there will be two canonical correlations. The canonical correlation is a tool used to measure the association between discriminant functions and the two motives. The canonical correlation between the first function and the two motives is very high which is 0.8, but canonical correlation for the second function is only 0.6. The Wilks Lambda table indicates that both canonical correlations are significant.

Wilks' lambda for the first function is 0.226 which indicates the group means are different in the first function which is the function of family oriented motive and Wilks lambda for second function is 0.636 which also indicates that group means are different but not to the extent of the first function. The second function is the function of self support motive where the group difference is less. A chi-square transformation of Wilks' lambda is used along with the degrees of freedom to determine the degree of significance. The significance value is small for the first function which is 0.000. It indicates that group means differ very much significantly in the first function which is represented by family oriented motive. The Chi-square value for the second function is 248.443 which is also significant by 0.000.

The structure matrix indicates that two functions can be formed for the three clusters. These two domain functions can be used separately, to describe the characteristics of population. The two domain functions are

Z1 = 0.994 * Family oriented motive--1

Z2 = 0.970 * Self Support motive.--2

Diagram 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.


The Classification of Results table measures the degree of success of the classification on the basis of motives. The number and percentage of cases correctly classified and misclassified are displayed in the table. Here 203 cases or 98.5 percent of highly motivated segments are correctly classified and only 3 cases are included in to self centered segment. In the least motivated segment 134 cases accounting for 97.8 percent are correctly classified. In self centered, it is 100 percent correctly classified. From this it can be clearly inferred that the segmentation of investors based on motive is correct by more than 98.9 percent.


It can be concluded from the above analysis that around 95 percent of Indians agree with the existence of motives to save and 75 percent of the people have high level of motivation to save. Another important finding of the study is that the level of motives has a significant influence on size of saving. India has high saving rate because Indians have high level of motives to save. The present high level of saving rate will continue as long as Indians have high level of motives. Hence the savings in India depends mainly on the ability to save. Understanding the requirements and characteristics of various segments, the marketers of investment products can tailor different instruments exclusively for different segments to fit their needs. This will help them to tide over the competition effectively and efficiently which might arise out of globalisation.


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Alagappa University, Karaikudi
Table 1
Priorities of Motives

S. No Motives Mean Value Rank

1 Precaution 3.95 I
2 Foresight 3.80 II
3 Improvement 3.45 III
4 Independence 3.35 IV
5 Pride 3.27 V
6 Calculation 3.16 VI
7 Avarice 2.42 VII
8 Enterprise 2.30 VIII

Table 2
KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of
Sampling Adequacy 0.731

Bartlett's Test of Sphericity Chi-Square 804.442
 df 28
 Sig. 0.000

Table 3
Factor Loadings for Self Support Motive

 Statements Factor Loading

1.1) I save because I desire to provide
 for anticipated future needs like old age. 0.762

(1.2) I save because I desire to build reserve 0.684
 for unforeseen contingencies.

(1.3) 1 save because I desire to enjoy an
 enlarged future income like interest
 and appreciation 0.654

(1.4) I save because I desire to meet gradually
 increasing expenditure in order to
 improve the standard of living 0.624

(1.5) I save because I desire to enjoy a
 sense of independence and power to do 0.609

Table 4
Factor Loadings for Family Oriented Motive

 Statements Factor Loading

(2.1) I save because I desire to carry out 0.830
 speculation business.

(2.2) I save because I desire to spend less 0.686
 (satisfy a purely miserly instinct)

(2.3) I save because I desire to pass the fortune
 to next generation (bequeath a fortune) 0.636

Table 5
Strength of Motives

S. No. Motive Mean Rank

1 Self Support 3.54 I
2 Family Oriented 2.66 II

Table 6
Self Support Motive

 Frequency Percent

Disagree 29 5.3
Agree 523 94.7
Total 552 100.0

Table 7
Family Oriented Motive

 Frequency Percent

Disagree 265 48.0
Agree 287 52.0
Total 552 100.0

Table 8
Variance Explained by Factors
 % Variance
S. No. Factors Eigen Value Explained Cumulative

1 Self Support Motive 2.597 29.337 29.337
2 Family Oriented Motive 1.604 23.173 52.510

Table 9


 1 2

Self Support 3.75(I) 3.37(II)
Family Oriented 3.38(I) 2.09(II)

Table 10
Final Cluster Centers

Motives Cluster

 1 2 3

Self Support 3.72(II) 2.81(III) 3.85(I)
Family Oriented 3.51(II) 2.12(III) 2.18(II)
Average 3.61 2.46 3.01

Table 11

Motives Cluster Error F
 Mean Square df Mean Square df

Self Support 50.253 2 0.283 549 177.428
Family Oriented 118.658 2 0.241 549 492.222

Motives Sig.

Self Support 0.000
Family Oriented 0.000

Table 12
Number of Cases in Each Cluster

Cluster 1 206.000 37%
 2 137.000 25%
 3 209.000 38%
Valid 552.000 100%

Table 13
Number of Cases in Each Cluster

Cluster 1 246.000 45%
 2 306.000 55%
Valid 552.000 100%

Table 14
Tests of Equality of Group Means

 Wilks' Lambda F df1 df2 Sig.

Self Support 0.607 177.428 2 549 0.000
Family Oriented 0.358 492.222 2 549 0.000

Table 15
Eigen Values

Function Eigen value % of Variance Cumulatiue % Correlation

1 1.809 75.9 75.9 0.802
2 0.573 24.1 100.0 0.604

Table 16
Wilks' Lambda

Test of Function(s) Wilks' Lambda Chi-square df Sig.

1 through 2 .226 814.879 4 0.000
2 .636 248.443 1 0.000

Table 17
Structure Matrix


 1 2

Family Oriented 0.994 * -0.112
Self Support 0.244 0.970 *

Table 18
Classification of Results

 Predicted Group Membership

 Saving Highly Least Self
 Motives Motivated Motivated centered

Original Count Highly Motivated 203 0 3
 Least Motivated 3 134 0
 Self centered 0 0 209
 % Highly Motivated 98.50 0.0 1.5
 Least Motivated 2.20 97.8 0.0
 Self centered 0.00 0.0 100.0

 Saving Total

Highly Motivated 206
Least Motivated 137
 Self centered 209
Highly Motivated 100.0
Least Motivated 100.0
 Self centered 100.0

98.9% of original grouped cases are correctly classified.
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Author:Kasilingam, R.; Jayabal, G.
Publication:Indian Journal of Economics and Business
Date:Dec 1, 2008
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