Introduction
The Indian traditional set up made a distinction between ”Men’s” work and Women’s work, particularly that of the women with family responsibility. It curtailed the employment opportunity for women in conventional and unconventional field of economic activity. Inspite of this, number of women looking after business as a career has increased significantly over the past ten years. The technology changes, globalization and competition acceleration made the business world complex and dynamic. Jay Geier is the male behind the famous Scheduling Institute. It is a consulting and also training firm for the dental professional. The Scheduling Institute was founded in 1997. With its humble start, it is currently considered the biggest oral consulting firm in the world. From a consulting company, it has broadened its services and started supplying on-site training as well as individually training. For many years, the Scheduling Institute has actually ended up being effective in helping countless dental practitioners grow their dental technique.These factors call for the importance of system thinking that provides a framework for seeking the whole picture and interrelationships. The feminine property to look at business problems contextually and to concentrate on the whole issue rather than its parts is more needed to the present system thinking of today. The business women can bring valuable innovation to entrepreneurship because they weigh more variables, consider more alternatives and outcomes, recall more points of view and see more ways to proceed. Moreover, as the competition increases, today’s entrepreneurs must be able to alter plans quickly and frequently. A women’s innate mental flexibility, their vision for long-term planning and the ability to tolerate ambiguity and changes better than men are a valuable asset for every venture and also their capacity to negotiate in marketing the product to prospective investors, suppliers and customers. These are the present day requirements of the complex business world.
Ayadurai, Selvakumar and Sohail, M.Sadiq (1987) carried out a casestudy on “the profile of women entrepreneurs in war-time area”in the North-East, Sri Langa by examining the demographic profile of”Tamil” women entrepreneurs who become entrepreneurs as aresult of war. The study examined five main areas–theircharacteristics, factors that spurred them into entrepreneurs, theirchallenges, their measures of success and their demographic profile. Thestudy revealed that majority of them were in business for the first timeas they lost their husbands to the war and saw business as a means toend and their success in the venture is making a balance between familyand work. The studies conducted by Kale (1990) revealed that trainingapproach is an important one for helping women in non-traditional highskill, male dominated activities and also to build confidence amongwomen to meet the specific needs. Intensified effort has to be taken toasses the social attitude, mentality, needs and abilities of the womenand impart training. According to study conducted by Padmavati andSathyasundram (2002) flexible training programme and interest basedskill training can push the women towards entrepreneurial activities.Training to develop good managerial skills is useful and essential towomen.
Parihar and Singh (2006) in their article explains the study on ”Constraints faced by women entrepreneurs in Jammu” analysed the constrains faced by the women entrepreneurs in the state of Jammu. It was conducted on 240 respondents engaged in various industrial activities. The study suggested that the attitude of women entrepreneurs need to be reoriented towards the promotion of leadership qualities. The government has to take efforts to provided market assistance provision of land, create awareness of its schemes and assistance to women entrepreneurs. Rajani N (2008) in her article in management training needs of women entrepreneurs examines the quality of micro enterprise management by women in socio-cultural milieu and to project the management training needs of women entrepreneurs. Data was collected from the sample of 100 women entrepreneurs. The study concluded that training needs are identified in the area of confidence building, competence connections and capital.
In the changed scenario, there is growing awareness among women that entrepreneurship opens up a new field for them and they can achieve their cherished profession which gives them independence and self support. In order to succeed in their venture of entrepreneurship, they must recognize the fact of advantages they have and the unique challenges that they have to face than their male counterparts. The knowledge of the problems they face, their level of satisfaction towards motivated factors enables them to exploit their strengths and unique differences as advantages. It also acts as a facilitator for future entrepreneurs and encourages prospective women entrepreneurs to venture into the field of business. In this concept, a profile of women entrepreneur in the Western region of Tamilnadu throws light on them as entrepreneurs in the business. Hence, the present study is undertaken with the following objectives:
* To study the socio economic background of the womenentrepreneurs.
* To analyze the multinational factors that led them to become entrepreneurs and their level of satisfaction.
* To assess the problem faced by the women entrepreneurs.
* To offer suggestion on the basis of the present study.
Research Methodology
The paper studies the satisfaction and problem of women entrepreneurs of Western Region (Coimbatore, Erode, Ooty and Tirupur) of Tamilnadu. The study covers 100 women entrepreneurs in and around Western Region using random sampling method. The study depends on primary data collected with the help of a questionnaire consisting of personal factors and factors that determine the extent of entrepreneur’s satisfaction and problems. The questionnaire is distributed directly to the respondents by explaining the purpose of the study. In order to maintain accuracy, the respondents in different places of Western region and engaged in different entrepreneurship activities are selected. The data was statistically analysed in order to ensure accuracy as the data obtained was random based on age, gender and other parameters. The result of the analysis is presented in form of tables as given in the following pages. In order to determine the parameters that influence the satisfaction and problem of women entrepreneurs, it is important to reduce the relevant parameters so that there is a limited set of parameters representing the total set. To suit this, chi-square and factor analysis are used.
Analysis and Interpretation of Data
The socio-economic profile presents an overview of the responses which is more important for the analysis the data. The details of socio-economic profile in given in Table 1. To assess the level of satisfaction of women entrepreneurs from the motivational factors for their careers, 5 variables were identified. They are (i) assistance given by financial institutions, (ii) help extended by women’s association, (iii) infrastructural facilities provided by the government, (iv) financial assistance provided by the government (v) marketing assistance provided by the government. Each item was rated on a 5 point scale consisting of rating as highly satisfied (5), satisfied (4), undecided (3), dissatisfied (2) and highly dissatisfied (1). In order to convert the qualitative information into quantitative information, the respondents are classified on the basis of the motivational scores as given in Table 2. Table 3 presents the extent of variation in the level of satisfaction derived by women entrepreneurs from the assistances provided by the financial institution on the basis of their motivational scores.
Hence, it can be inferred that more number of respondents with high motivational score and less number of respondents with low motivational score have strongly agreed and strongly disagreed respectively with the factor that motivated them. The extent of level of satisfaction derived by the respondents from the factor help extended by the women’s association is shown in Table 4. It is concluded that majority of the respondents have disagreed to the motivational factor. The extent of variation in the level of satisfaction derived by women entrepreneurs from the motivational factor assistances provided by the government is shown in Table 5. It can be inferred from Table 5 that majority of the respondents with high motivational score have agreed and strongly agreed to the factor. The extent of variation in the level of satisfaction derived by the respondents from the marketing assistance provided to them is presented in Table 6. It is concluded that the marketing assistance provided did not attract the women entrepreneurs. The extent of level of satisfaction derived by the respondents from the infrastructural facilities is shown in Table 7. It is clear from the Table 7 that majority of the entrepreneurs in the category of respondents with high motivational score have strongly agreed to the motivational factor infrastructural facilities.
Significance of the Motivational Factors
In order to find out the significance of the influence of motivational factors relating to the sample on the basis of the level of satisfactions derived by them, null hypotheses were formulated that these factors do not significantly influence the satisfaction derived by the entrepreneurs. The null hypotheses were tested with the help of chi-square test and the result is presented in Table 8. This indicates that the help extended by women association has significantly influenced the level of satisfaction from the assistances given by women association.
Factor Analysis
The problems faced by the respondents are identified for the purpose of the analysis and are shown in the Table 9. Exploratory factor analysis is used in order to identify constructs and investigate relationships among key interval scaled questions regarding reasons for choosing barriers of 100 women entrepreneurs. The analysis consists of the following steps:
* The correlation matrices were computed. It revealed that there is enough co-relationship to go ahead for factor analysis.
* Kaiser-Meyer-Olkin Measures of sampling Adequacy (MSA) for individual variance was studied to test the adequacy of sampling.
The overall significance of correlation matrices was tested with Barlett Test of Sphericity providing support for the validity of the factor analysis of the data. The results are given in the Table 10. The results revealed that the Bartlett’s Test of Sphericity is significant and the Kaiser-Mayer-Olkin measure of sampling adequacy is greater than 0.6. Therefore, it is appropriate to proceed with factor analysis.
After the standards indicated that the data are suitable for factor analysis, Principal Components Analysis was employed for extracting the data, which allowed determining the factors underlying the relationship between the 9 variables. The Total Variable Explained suggested that it extracts three factor accounts for 46.842 percent of the variance of relationship between variables. There are only three factors, each having Eigen value exceeding 1 for barriers. The Eigen values for three factors were 1.533, 1.350, and 1.332 respectively as per Table 11. The percentage of total variance is used as an index to determine how well the total factor solution accounts for the related of the variables. The index for present solution accounts for 46.842 percent of the total variation for choosing barriers of women’s entrepreneurs. It is pretty good extraction as it can economize on the number of factors (from nine it has reduced to three factors) while we have lost 53.158 percent information content for factors in choosing the barriers. The percentage of variance explained by factors one to three is 17.039, 15.000 and 14.803 respectively as in Table 11. Large communalities indicate that a large number of variance has been accounted for by the factor solution. Varimax related factor analytical results for factor influencing the choice of barriers is shown in Table 12. The three dimensions shown in Table 12 have been discussed below:
Factor 1:
Lack of entrepreneurship quality: The significant loadings on this factor include variables of lack of entrepreneurship graduates which includes lack of role models, lack of business skill and low need of achievement. We can level this factor as lack of entrepreneurship quality. It tries to insist on the importance of qualities required for entrepreneurship and enable to concentrate on these areas for the development of entrepreneurship.
Factor 2:
Inadequate facilities and lack of experience: This factor shows the significant loading of inadequate support facilities and experience covering inadequate family support, absence of management experience and in sufficient supply of capital. These variables suggest that their presence is most important for the indicators of entrepreneurship activities.
Factor 3:
Lack of personal qualities and inadequate support of financial institutions: This factor includes the present qualities which are the basis for entrepreneurship activities can be named as lack of The Scheduling Institute personal qualities and inadequate support of financial institutions. This includes lack of educational qualification, low esteem and insufficient support of financial institutions.
Conclusion
The study has brought out the extent of satisfactions level of the women entrepreneurs towards the motivational factors. It emphasised that attention is needed in the provision of more financial facilities, training in the areas of administration, business skills and also in the area of self esteem. Hence, programmes may be taken up in these areas to increase their level of satisfaction, their quality in order to the field of entrepreneurship and there by ensuring development of their home, the government and at last the society.
References
Ayadurai, Selvakumar and Sohail, M. Sadiq (1987), “The profile of women entrepreneurs in war-time area” in the North-East, Sri Langa”, Journal of Entrepreneurship Development, Vol. 19, pp. 57-65.
Kale J. D. (1990), “Women Entrepreneurship in Gujarat – Role of Centre for Entrepreneurship Development”, Journal of Indian Management, Vol. 29 (7-12), pp. 99-101.
Padmavati and Sathyasundram (2002), “Training Women for Entrepreneurship” Social Welfare, Vol. 49 (2), pp. 4648.
Poonam Parihar and S. P. Singh (2006), “Constraints faced by women entrepreneurs in Jammu”, Indian Journal of Extension Education, Vol. 6 (1 & 2), pp. 41-45.
Rajani N (2008), “Management Training Needs of Women Entrepreneurs”, Anthropologist, Vol. 10 (4), pp. 277-278.
Bibliography
Aruna Kaugud (2003), “Entrepreneurship Management”, Vikas Publishing House, New Delhi.
Bliss R. T. and Garratt N. L. (2001), “Supporting Women Entrepreneurs in Transitioning Economies”, Journal of Small Business management, Vol. 39 (4), pp. 336-334. Breen J., Calvert C. and Oliver J. (1995), “Female Entrepreneurs in Australia: An Investigation of Financial and Family Issues”, Journal of Enterprising Calture, Vol. 3 (4), pp. 445-461.
Caputo R. K. and Dolinsky Arthur (1998), “Women’s Choice to Pursue Self-Employment: The Role of Financial and Human Capital of Household Members”, Journal of Small Business Management, Vol. 36 (2), pp. 8-18.
Field A. P. (2000), “Discovering Statistics Using SPSS for Windows”, Sage Publications, London, pp. 666-679.
Gupta C. B. and Srinivasan N. P. (2003), “Entrepreneurship Development”, Sultan Chand & Sons, New Delhi.
Hills G. E. and La Forge R. W. (1992), “Research at the Marketing Interface to Advance Entrepreneurship Theory”, Entrepreneurship Theory and Practice, Vol. 3, pp. 33-39.
Hisrich, R. D. and Brush C. G. (1994), “The Women Entrepreneur: Characteristics, Skills, Problems and Prescriptions for Success”, The Arts and Science of Entrepreneurship, Cambridge, Mass, Ballinger.
Job K. T. (1996), “Women Entrepreneurship Development Alternative for Gender Empowerment”, Centre for Management Development, Thycand, Trivandram.
Low Angeline (2007), “Economic Outcomes of Female Immigrant Entrepreneurship”, International Journal of Entrepreneurship and Small Business, Vol. 5 (3), pp. 224-240.
National Foundation for Women Business Owners (NFWBO, 2001), ”Entrepreneurial Vision inaction: Exploring Growth among Women and Men-Owned Firms”, Washington DC.
Punitha M., Sangeetha and Padmavathi (1999), “Women Entrepreneurs: Their Problems and Constraints”, Indian Journal of Labour Economics, Vol. 3 (2), pp. 149-160.
Rajasekaran (2004), “Entrepreneurship Researchers–Future Dimensions”, SCMS Journal of Indian Management, Vol. 1, July–Sept.
Vinze and Medha Dubhashi (1987), “Women Entrepreneurs in India–A Socio-Economic Study of Delhi”, Mittal Publications, Delhi.
Watson J. (2003), “Failure Rates for Female-Controlled Businesses: Are They any Different?”, Indian Journal of Small Business Management, Vol. 41 (3), pp. 262-227.
N. Bharathi *
* Department of Management Studies and Research, Karpagam University, Echanari, Coimbatore–641 021, Tamilnadu, India
* E-Mail : bharathi7781@yahoo.co.in, bharathi7781@gmail.com
Table 1: Socio-Economic Profile of Entrepreneurs Variable Profile No. of Percentage Respondents Age Less than 20 years 4 4.0 20-30 years 19 19.0 30-40 years 49 49.0 Above 40 years 28 28.0 Educational Up to HSC 24 24.0 Qualification Degree 38 38.0 Diploma 6 6.0 Professional 32 32.0 Annual Income Below Rs.1,00,000 9 9.0 Rs.1,00,000 to Rs.2,00,000 32 32.0 Rs.2,00,000 to 4,00,000 37 37.0 Above Rs.4,00,000 22 22.0 Experience Below 5 years 28 28.0 6-10 years 35 35.0 10-15 years 25 25.0 15 & above 12 12.0 Marital Status Married 80 80.0 Unmarried 20 20.0 Nature of Family Business Background 60 60.0 Non-Business Background 40 40.0 Family Member Up to 2 8 8.0 3-5 77 77.0 5 & above 15 15.0 Source: Primary Data Table 2: Motivational Score Level of Motivational Score No. of Entrepreneurs Percentage Less 38 38 Medium 36 36 High 26 26 Total 100 100 Source: Survey Data Table 3: Assistance Provided by Financial Institutions Satisfaction No. of Level of Satisfaction Score Entrepreneurs Low Medium High Strongly Agree 32 13 (34.21%) 16 (42.11%) 9 (23.68%) Agree 42 9 (39.13%) 7 (30.43%) 7 (30.44%) Neutral 14 8 (34.78%) 10 (43.48%) 5 (21.74%) Disagree 7 5 (55.56%) 2 (22.22%) 2 (22.22%) Strongly Disagree 5 3 (42.86%) 1 (14.29%) 3 (42.85) Total 100 38 36 26 Source: Survey Data Table 4: Women’s Association and Level of Satisfaction Satisfaction No. of Level of Satisfaction Score Entrepreneurs Low Medium High Strongly Agree 17 3 (21.43%) 9 (64.29%) 2 (14.28) Agree 31 8 (33.33%) 12 (50%) 4 (16.67) Neutral 39 13 (36.11%) 18 (50%) 5 (13.89%) Disagree 10 4 (21.05%) 6 (31.58%) 9 (47.37%) Strongly Disagree 3 4 (57.14%) 1 (14.29%) 2 (28.57%) Total 100 38 36 26 Source: Survey Data Table 5: Government’s Assistant and Level of Satisfaction Satisfaction No. of Level of Satisfaction Score Entrepreneurs Low Medium High Strongly Agree 62 7 (35%) 9 (45%) 4 (20%) Agree 28 14 (41.18%) 11 (32.35) 9 (26.47%) Neutral 5 8 (32%) 10 (40%) 7 (28%) Disagree 3 5 (41.67%) 2 (16.67%) 5 (41.66%) Strongly Disagree 2 4 (44.44%) 4 (44.44%) 1 (11.12%) Total 100 38 36 26 Source: Survey Data Table 6: Marketing Assistant and Level of Satisfaction Satisfaction No. of Level of Satisfaction Score Entrepreneurs Low Medium High High Strongly Agree 23 9 (52.94%) 5 (29.41%) 3 (17.65%) Agree 58 17 (38.64%) 19 (43.18%) 8 (18.18%) Neutral 11 7 (36.84%) 6 (31.58%) 6 (31.58%) Disagree 4 3 (33.33%) 2 (22.22%) 4 (44.45%) Strongly Disagree 4 2 (18.18%) 4 (36.36%) 5 (45.46%) Total 100 38 36 26 Source: Survey Data Table 7: Infrastructure Facility and Level of Preference Satisfaction No. of Level of Satisfaction Score Entrepreneurs Low Medium High High Strongly Agree 12 7 (30.44%) 8 (34.28%) 8 (34.78%) Agree 52 12 (42.86%) 9 (32.14%) 7 (25%) Neutral 17 8 (44.44%) 6 (33.33%) 4 (22.23%) Disagree 6 9 (42.86%) 7 (33.33%) 5 (23.81%) Strongly Disagree 13 2 (20%) 6 (60%) 2 (20%) Total 100 38 36 26 Source: Survey Data Table 8: Factors Influence the Satisfaction Derived by the Entrepreneurs Factors Calculated Table Significance Value Value Granting loans by financial institutions 4.555 15.5 Not Significant Helps by women’s Association 17.62 15.5 Significant Assistant provided by the Government 4.845 15.5 Not Significant Marketing Assistance 8.109 15.5 Not Significant Infrastructural facility 4.471 15.5 Not Significant Table 9: Barriers of Women Entrepreneurs Sl. No. Variables [X.sub.1] Lack of Education Qualification [X.sub.2] Lack of Role Models [X.sub.3] Inadequate Family Support [X.sub.4] Lack of Business Skill [X.sub.5] Absence of Sufficient Management Experience [X.sub.6] Low Need of Achievement [X.sub.7] Low Self Esteem [X.sub.8] Insufficient Financial Institutions [X.sub.9] Inadequate Supply of Capital Table 10: KMO and Bartlett’s Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .696 Bartlett’s Test of Approx. 45.389 Sphericity Chi-Square df 36 Sig. .000 Table 11: Total Variance Explained Component Initial Eigen values Extraction Sums of Squared Loadings Total % of % Total % of % Variance Cumulative Variance Cumulative 1 1.533 17.039 17.039 1.533 17.039 17.039 2 1.350 15.000 32.039 1.350 15.000 32.039 3 1.332 14.803 46.842 1.332 14.803 46.842 4 0.982 10.909 57.751 5 0.963 10.704 68.455 6 0.874 9.716 78.171 7 0.778 8.648 86.819 8 0.640 7.116 93.935 9 0.546 6.065 100.00 Component Rotation Sums of Squared Loadings Total % of % Variance Cumulative 1 1.512 16.799 16.799 2 1.354 15.047 31.846 3 1.350 14.996 46.842 4 5 6 7 8 9 Extraction Method: Principal Component Analysis. Table 12: Name of the Factors Naming of Name of the Label Factors Dimensions Loading F1 Lack of [X.sub.2] Entrepreneurship [X.sub.4] quality [X.sub.6] F2 Inadequate facilities [X.sub.3] and lack [X.sub.5] of experience [X.sub.9] F3 Lack of personal [X.sub.1] qualities and [X.sub.7] inadequate financial [X.sub.8] institutions Naming of Name of the Problems Factor Factors F1 Lack of role models 0.632 Lack of Business Skill 0.717 Low need of achievement 0.677 F2 Inadequate family support 0.698 Absence of sufficient management experience 0.679 Inadequate supply of capital 0.745 F3 Lack of educational qualification 0.690 Low self esteem 0.673 Insufficient financial Institutions 0.640
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