"The Affluent Women Entrepreneurs in Tamil Nadu:
Motivational Factors"
An Empirical Study


By

Dr. N. Panchanatham
Ph.D
Reader & Head
Department of Business Administration
Annamalai University
Chidambaram–608002

V. Vijay Anand,
Ph.D - Research Scholar & Asst. Professor
K.A. Shreenivasan
Ph.D - Research Scholar & Asst. Professor
School of Management
SASTRA University
Thanjavur–613401
 


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Factors responsible for choice of product

Factors responsible for choice of Product line

Factors

% of total

1. High Demand

51.0

2. Possessing Skills

30.2

3. Ready market

30.1

4. Future Prospects

24.0

5. Requiring creativity

23.9

6. Typically 'feminine'

17.7

7. Socially accepted

17.6

8. Past experience in line

15.5

9. Family business

13.5

10.Less Mobility required

11.5

11. Lower Cost

9.3

12. Short Gestation period

5.2

13. High rate of return

5.2

14. Any other

---


Source : Primary Data

From a list of 13 possible factors, the respondents were asked to identify factors responsible for choice for their product line .

A glance at the first four factors indicates a clear professional attitude towards selection of the product line.  This is reinforced by the fact that low priorities have been given to factors like short gestation, high rate of return, lower cost, less mobility required etc.  At the same time low priority has also been given to factors like "typically feminine" and "socially accepted" activities.  From the sample, it is evident that past experience in the line has been given a low priority (15.5%). 

Project Selection

It is generally believed that whenever women venture into business, the preference is given to non-technical or feminine activities involving skills that women generally possess.  Along with this, the trend of thinking is that women prefer the safer trading and service industry.  However, the table 11 below dispels these myths. 

Table No :2

Type of products taken by the respondents

Type of products

% of total

1. Food Products

3.3

2. Chemical, Rubber & Plastics

8.3

3. Printing & Paper Products

6.7

4. Leather

3.3

5. Handloom & Garments

21.7

6. Textile

8.3

7. Beauty Clinics

8.3

8. Consultancy

5.0

9. Electronics & Electrical Equipment

13.3

10. Stainless Steel Utensils

3.3

11. Machinery

10.0

12. Other item (Photostat, Wooden toys)

8.3


Source : Primary Data

For example, 21.7% of respondents were involved in handloom and garment manufacturing, followed by electronics and electrical equipment (13.3%).  This is followed by machinery  (10.0%) chemicals, rubber and plastic, textiles and beauty clinic and other items falls in the next place (8.3% each).  Another interesting finding is that food products, Leathers and stainless steel utensils figured at 3.3 % each.

Activity and sources of help

The survey also proves beyond doubt that women do not stick to the safer trading and service industry.  Majority of the sample (70.0%) went in for manufacturing, followed by service industry (16.7%) and trading (13.3%).  A further analysis vis-à-vis their educational background reveals that majority of the women who went in for manufacturing was simple graduates (45.2%) followed by undergraduates (31.0%).  Very few women (14.3%) had professional qualifications, and yet went in for manufacturing.  Graduates again had the lead in trading activities.  In our sample, 100% of the women who were engaged in trading were graduates.  Graduates again accounted for 40.0% of those women engaged in service industry like beauty clinics etc.  As a matter of fact, a majority of the sample (51.7%) were graduates, followed by undergraduates (26.7%).  Professionals only accounted for 13.3% of the total sample, whereas only 8.3% of women were post-graduates.

The fact that a majority of women are only graduates, and have mostly taken to manufacturing raises a serious doubt about their intentions. Does it mean that the business is only taken lightly, considering most women do not have financial problems?  This, coupled with the finding, the majority have entered into business just to keep busy strengthens this premise.  This is further strengthened by the fact that 48.3% of the sample had gone in for training, whereas 51.7% were untrained. If their businesses are doing well despite a lack of expertise on their part, and an obvious dependency upon others, could they not expect greater gains by professionalism? One sees a sense of complacency in this kind of an attitude.

Table No: 3

Distribution of respondents according to background

Training

% of total

Trained Women

48.3

Untrained Women

51.7

Help Taken

% of total

Women operating independently

36.7

Women taking male help

63.3


Source : Primary Data

From the above it is clear that majority of women have to depend upon someone to help them in their day-to-day activities.  On enquiries it was found that 36.7% of women have taken no help and are independently running their business, whereas 63.3% of women entrepreneurs do depend upon male help.  A look at the table shows a direct correlation between training and dependency upon male help.  While this does not mean that it is only trained women who are independent of male help, or vice versa, but clear trend emerges which indicates that with a higher incidence of training, there could be a possibility of with lower dependence on male help.

Table No : 4

Distribution of respondents on the basis of help received (%)

Kind of Help

Manufacturing

Trading

Service

Total

Sales & Marketing

66.6

33.4

---

17.7

Liaison and Field Work

83.3

16.7

---

17.7

Accounts

80.0

20.0

---

14.7

Moral & General

66.6

---

33.4

8.8

Administration

71.4

7.17

21.4

41.1

Total

73.5

14.7

11.8

100.0


Source : Primary Data

Regarding the kind of help that the sample has taken, it was found that majority (41.1%) pertained to moral and general administration help, provided mostly by husbands.  Women tend to depend upon male help for sales and marketing (17.7%) liaison and field-work (17.7%), technical (14.7%) and accounts (8.8%).

Awareness of Incentives

Training makes entrepreneurs more aware of their environment, and of the facilities and incentives offered by the Government, to give encouragement to women entrepreneurs.  This evident from the table below:

Table No : 5

Respondents awareness to incentives

Training

Awareness of Special Incentives

Total

Aware

Partially Aware

Not Aware

 

Trained

27.6

24.1

48.3

 

48.3

Untrained

19.4

6.5

74.2

 

51.7

Total

23.3

15.0

61.7

 

100.0


Source : Primary  Data

Of the trained entrepreneurs 51.7% were either aware or partially aware of the special incentives for women entrepreneurs; where are 74.2 % an overwhelming majority of untrained women entrepreneurs, were not at all aware of the incentives meant for them.  But it is surprising to note that very few has availed special incentive.  On discussions with the respondents, the general feeling was that those incentives only existed in paper and that the formalities for availing then were too many and complicated.  On probing deeper, some respondents admitted that they had no time to find out about these schemes.  Others who were better read, and had subscribed to various journals pertaining to industry finance, management, etc. claimed that no mention of these special incentives appeared anywhere in them.  They generally felt that not enough publicity was being given to such incentives to attract women entrepreneurs.
 

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Source: E-mail January 8, 2011

          

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