Chapter one introduction 1 Background to the Study



Download 3.04 Mb.
Page10/18
Date conversion08.07.2018
Size3.04 Mb.
1   ...   6   7   8   9   10   11   12   13   ...   18

3.11 Validity of the Research Instrument

Validity test was carried out so as to ensure that the research instrument measured what it was supposed to measure. The four methods of measuring external validity are: face validity (Selltiz et al, 1976; Phillips, 1976 and Bailey, 1987); content validity (Goode and Hatt, 1952; Kerlinger, 1964; Bailey, 1987; Singleton et al, 1993); criterion validity (Phillips 1976; Selltiz et al 1976; and Bailey 1987) and construct validity (Stevens 1951, Kerlinger 1964 and Bailey 1987, Singleton et al, 1993). Face and content validity were carried out on this work. Content validity measures the appropriateness of the wording of the instrument and the objectives of the study while the face validity enables the researcher to make an assertion to claim to have measured what he or she intended to measure (Stevens, 1951). The validity measurement of this study was justified using the works of Levine (1981), Kerlinger (1983), Bailey 1987, Ekpo-Ufot (1992), Singleton et al, (1993). To ensure face and content validity of the instrument (content-related evidence), senior academics on entrepreneurship and enterprise development studies, specialists and experts on the topic of research measured by the instrument were asked to make their inputs and judge the appropriateness of the items on the instrument. This is to find out if the instrument covered the breath of the content area (and to ascertain if the instrument contains a representative sample of the content being assessed). The researcher also confirmed if the format used in designing the instrument is appropriate for obtaining the information required from the respondents.



3.12 Reliability of the Research Instrument

Reliability test ensures that the instrument measures consistently as required by this work. It also shows the extent to which the researcher can confidently rely on the information obtained through the use of the instrument adopted to gather data for the research work. Consequently, data collected were subjected to reliability analysis to establish the reliability of the measures and ensuring consistent measurement among the various items in the instrument (Goode and Hatt, 1952, Kerlinger, 1964, Phillips, 1976, Selltiz et al, 1976, Bailey, 1987, Singleton et al, 1993). Analysis to the reliability of coefficient showed that Cronbach Alpha for all variables under revalidation and this met Nunally’s (1978) suggestion of 0.50 or above criterion. The reliability measures were justified using the works of Goode and Hatt (1952) and Zikmund (1994). Three major categories of reliability test were carried out to ensure the reliability of the instrument. These include test-retest, equivalent form, and internal consistency. Each of these reliability test measures consistency a bit differently. For instance, test-retest measures consistency from one time to the next. Equivalent-form measures consistency between two versions of an instrument. Internal-consistency measures consistency within the instrument (consistency among the questions).

(i) To ensure test-retest, the instrument was given the second time to the same group of respondents, reliability was confirmed through the correlation between the scores on the two independent instruments.  The purpose of test-retest reliability is to determine the period of time to wait between the two administrations. In fact, we waited long enough to ensure that the subjects do not remember how they responded the first time they completed the instrument and also ensure that it was not too long a time to influence change in the knowledge of the material being measured. In fact the test-retest was carried out within one month interval. This was calculated using Crobanch Alpha with Statiscal Package for Social Sciences (SPSS) and the result yielded r = 0.67

(ii) To ensure equivalent-form (parallel or alternate-form) validity, two different versions of the instrument were created. Apart from administering the instrument to the women entrepreneurs, the same instrument was administered to some men entrepreneurs. The researchers assumed that the two instruments measure the same thing. The respondents completed the instruments during the same time period. The scores on the two instruments were correlated to calculate the consistency between the two forms of instruments and the result yielded r=0.64 using Cronbach Alpha with SPSS.

(iii) The internal-consistency of the instrument or split half method was also used. The total score for the odd number statements was correlated with the total score for the even number statements. The Spearman-Brown Prophecy Formula was applied to the correlation to determine the reliability. Cronbach's Alpha was equally used because the items on the instrument were not scored as “right versus wrong”. Cronbach's alpha is often used to measure the internal consistency. This was calculated with SPSS and the result yielded r= 0.70

3.13 Method of Data Analysis

Data collected were analyzed with both manual and electronics based methods using a data preparation grid and SPSS. The utilization of structured grids allowed specific responses to be located with relative ease and facilitate the identification of emerging patterns (Munn and Drever, 1990). Descriptive, statistical and content analyses were used in analyzing the collected data (Asika, 2001; Osuagwu, 2002; Otokiti, Olateju and Adejumo, 2007). Using descriptive analysis we were able to calculate; the mean, frequency distribution and percentage analysis of the study. Statistically, the researcher was able to utlized the following statistical tools: Analysis of Variance (ANOVA), Chi-square, correlation coefficient and factor analysis in testing stated hypotheses. For example, (i) ANOVA: The Analysis of Variance was used in testing the hypothesis one. This enabled the researcher to analyze the degree of variance between two variables (independent and dependent variables) of the tabulated data. The total variance is partitioned into the variance which can be explained by the groups of independent variables (Between) and the variance which can be explained by all the units of the independent variables (Within) and the Sums of Squares for the Between and Within add up to the Total, reflecting the fact that the Total is partitioned into Between and Within variance. Sums of Squares are usually associated with the three sources of variance, Total, Between and Within. Degree of freedom is associated with the sources of variance.  The total variance has N-1 degree(s) of freedom.  The between degree of freedom corresponds to the number of groups minus 1 (K-1).  In this case, it is 4-1 (since there were 4 independent variables).  The Within degrees of freedom is the ‘df total’ minus the ‘df between’. Mean Square is the Sum of Squares divided by their respective ‘df’.   These are computed so as to find the F-ratio, dividing the Mean Square between by the Mean Square within to test the significance of the independent variables on dependent variables.

(ii) Similarly, Chi-square was considered appropriate for the analysis of the study. This became necessary for multinomial probability in which the sample size of the study was randomly selected to establish the relationship between women motivational factors and their performance in business. This was used in analyzing hypothsis two. (iii) Coefficient correlation which measures the relationship between two variables was used in testing hypotheses one, two, three, four and five. The Pearson Product-Moment Correlation Coefficient (r) is a measure of the degree of linear relationship between two variables, usually labeled independent and dependent. In correlation, the emphasis is on the degree to which a linear model may describe the relationship between two variables and the interest is non-directional, the relationship is the critical aspect. The coefficient of correlation can vary from positive one (indicating a perfect positive relationship) through zero (indicating the absence of a relationship) to negative one (indicating a perfect negative relationship).

Motivation and variables such as business performance, type of business ownership, challenges women face in business and environmental factors were tested using the correlation analysis. (iv) Factor analysis was also used to reduce the volume of the questions in the questionnaire into a smaller unit for easy usage in the analysis. This technique requires a large sample size before their stabilility can be managed. This is based on the report of Tabachnick and Fidell (2001). Factor analysis was used to reduce the factors motivating women entrepreneurs into four (social, psychological, financial and environmental). Factor analysis is a method of data reduction.  It does this by seeking underlying unobservable (latent) variables that are reflected in the observed variables (manifest variables). There are many different methods that can be used to conduct a Factor Analysis (such as principal axis factor, maximum likelihood, generalized least squares and unweighted least squares). There are also many different types of rotations that can be done after the initial extraction of factors, including orthogonal rotations, such as varimax and equimax, which impose the restriction that the factors cannot be correlated, and oblique rotations, such as promax, which allow the factors to be correlated with one another.


This study also adopted the usage of the Lorenz Curve to determine the degree of concentration and diversification in the spread of entrepreneurship. This technique was propounded by Lorenz (1905). It was used in economics and ecology to describe inequality in wealth distribution (Kotz et al, 1983). It can also be used to determine the nature or size of industrial concentration and diversification (Otokiti, 2005). The Lorenz Curve functioned as the cumulative proportion of ordered individuals mapped into the corresponding cumulative proportion of their size. Through its graphical representation of the proportionality of a distribution (the cumulative percentage of the values) all the elements of a distribution were ordered from the most important to the least important. Then, each element plotted according to their cumulative percentage in a graph of X and Y, X being the cumulative percentage of elements and Y being their cumulative importance. In this study, Lorenz Curve was used to determine the concentration or otherwise of women entrepreneurs in the three states used as the case study of this research work.
References
Amit, R., Glosten, L. and Muller, E.(1993) “Challenges to Theory of in Entrepreneurship

Research”. Journal of Management Studies, Vol. 30:5, 815-833.


Asika, N. (1991). Research Methodology in the Behavioural Sciences. Ibadan: Longman

Nigeria, Plc.


Bailey, K.D. (1987). Methods of Social Research. 3rd Edition, New York: The Free Press.
Bannock, G. (1981). The Economics of Small Firms: Return from the Wilderness, Basil

Blackwell, Oxford.


Bartlett, J. E., Kotrlik, J. W. and Higgins, C. C (2001). Organizational Research:

Determining Appropriate Sample Size in Survey Research. Information Technology, Learning, and Performance Journal, Vol. 19, No. 1, Spring, 43-50


Brockhaus, R. H. (1986). “Risk Taking Propensity of Entrepreneurship”. Academy of

Management Journal, Vol. 23, No. 3.
Brockhaus, R.H. and Horwitz, P.S. (1986). The Psychology of the Entrepreneur In D.L.

Sexton, and R.W. Similor (EDs), Women-owned Business, New York, Praeger, Pp. 55-75.


Brunstein, J. C., and Maier, G. W. (2005). “Implicit and self-attributed motives to

achieve: Two separate but interacting needs”. Journal of Personality and Social Psychology, 89, 205-222.


Chein, I. (1981). An Introduction to Sampling. In Research Methods in Social Relations,

4th ed., L. H. Kidder. New York: Holt, Rinechart and Winston.


Czaja, R. (1998). “Questionnaire Pretesting Comes of Age”, Marketing Bulletin, Vol. 9,

Pp. 52-66.


Denison, D. and Alexander, J. (1987). "Patterns and Profiles of Entrepreneurs:

Data from Entrepreneurship Forums". Frontiers of Entrepreneurship Research. Ed. Robert Ronstadt, Robert Hornday, Rein Peterson, and Karl Vesper. Wellesley, Mass.: Babson Center for Entrepreneurial Studies, 578-593.


Dubini, P. (1988). "The Influence of Motivations and Environment on Business Startups:

Some Hints for Public Policies". Journal of Business Venturing 4, 11-26.


Dunkelberg, W. C. and A. C. Cooper (1982). Entrepreneurial typolo­gies. In K. Vesper (Ed), Frontiers of entrepre­neurship, Wellesley, MA: Babson Center for Entrepreneurial Studies, 1-15.
Ekpo-Ufot, A. (1992). The State of the Arts of Finance-Accounting Management in

Some Lagos Organizations in the Chemical Industry: An Exploratory Study, in Ojo, J. A. T. (ed.), Business Performance Improvement Through Cost Management, Lagos: University of Lagos Press.


Gartner, W. B., Mitchell, T. M. and Vesper, K. H. (1989). A Taxonomy of New Business

Ventures. Journal of Business Venturing, Vol. 4, No. 3, 169-186.


Gelin, M. (2005). “The Importance of Gender in Starting and Managing a Small

Business”. Houston Psychiatric Society, June.


Goode, W. J. and Hatt, P.K. (1952). Methods in Social Research. New York: McGraw-

Hall.
GEM, (2005). “Report on Women and Entrepreneurship”, Global Entrepreneurship



Monitor.
Hisrich, R. D. and C. Brush (1986) “Characteristics of the Minority Entrepreneurs”,

Journal of Small Management, Vol. 24.
Hisrich, R. D., Micheal P. P. and Shepherd, D. A. (2005). Entrepreneurship,

International. Ed., Boston: McGraw-Hill,
Holton, E. H., & Burnett, M. B. (1997). Qualitative Research Methods. In R. A.

Swanson, & E. F. Holton (Eds.), Human Resource Development Research Handbook: Linking Research and Practice. San Francisco: Berrett-Koehler Publishers.


Keeble, D., and Walker, S. (1994). “New Firms, Small Firms and Dead Firms: Spatial

Patterns and Determinants in the United Kingdom”, Journal of Religious Studies,, Vol. 28, No 4.


Kerlinger, F. (1983). Foundations of Behavioural Research. New York: Holt, Rinehart

and Winston.


Kotz, S., Johnson, N. L. and Read, C. B. (1983). Encyclopedia of Statistical Science.

New York: Wiley.


Levine, R.J. (1981). Ethics and Regulations of Clinical Research. Baltimore: Urban and

Schwarzenberg.

Lorenz, M. O. (1905). Methods for Measuring the Concentration of Wealth. Amer. Stat.

Assoc. 9, 209- 219.


Minnit, M. , Allen, E., and , Langouitz, N. (2006). “Global Entrepreneurship Monitor,

2005 Report on Women and Entrepreneurship”. GEM Publication.


Miskin, V:, and Rose, J. (1990). Women Entrepreneurs: Factors Related to Success.

Frontiers of Entrepreneurship Research 1990. Gender, Work and Organization, 6(4), 224–235.


Mokry, B.W., (1988), “Entrepreneurship and Public Policy: Can Government

Stimulate Start ups?” Quorum Books, New York.
Munn, P. and Drever, E. (1990). Using Questionnaires in Small-Scale Research: A

Teacher's Guide. Loanhead: Macdonald Lindsay Pinder.
Nunally, J. C. (1978). Psychometric Theory, 2nd Edition. New York: McGraw Hill.
Ogundele, O. J and Opeifa, A. Z. (2003). “Factors that Influence the Emergence,

Behaviour and Performance of Entrepreneurs in Nigeria”, The Abuja Management Review, Vol.1, Issue No. 2, June.


Ojo, J.A.T. (2006). “Using SMEs To Achieve Millennium Development Goals:

Challenges and Prospects”. Covenant Journal of Business and Social Sciences,

Vol. No 1, December, 20-35
Olutunla, G. T.(2001). “Entrepreneurship for Economic Development:. Inaugural

Lecture Series 27, Delivered at the Federal University of Technology, Akure, Thursday, 26th April.
Orhan, M. and Scolt, D. (2001). “Why women enter into Entrepreneurship: An

Explanatory Model”. Women in Management Review, August, Vol. 16, Issue 5.


Otokiti, S. O. (1987). “High Technology in Small Scale Industries: A Comparative Study

of Nigeria and Industrialized Countries”. Ph.D. Thesis submitted to University of Delhi, New Delhi, India.


Otokiti, S. O. (2005). Methodologies and Mechanics of Computational System. New

Delhi India, Sultan Chand and Sons.


Otokiti, S.O., Olateju, O. and Adejumo, O. (2007). Contemporary Statistical Methods.

Lagos: Vantage Publication Company.

Osuagwu, L. (2002). “The Marketing Research Practices of Nigerian Companies: An

Exploratory Study”, Journal of African Business, Vol. 3(1), Pp. 81-107.


Oyo State of Nigeria, (2005). “Statistical Year Book 2003-2005, Department of

Macrostatistics and Research, Ministry of Finance, Budget and Planning Ibadan, Oyo State, Nigeria. 1-105.


Phillips, B. S. (1976). Social Research: Strategy and Tactics. 2nd Ed. New York:

Macmillian.


Ronstadt, R. (1984). “The Corridor Principle”. Journal of Business Venturing, Vol. Pp.

3:31-40
Rosin, H. and Korabit, K. (1990). "Marital and Family Correlates of Women Managers'

Attrition from Organizations”. Journal of Vocational Behavior, 37, 104-120.
Ryna, R. M. and Deci, E. (2002). “Intrinsic and Extrinsic Motivation: Class Definitions

and New Directions, Contemporary Educational Psychology”. Vol. 25, Issue 1,

January, Pp.54-67
Sarri, K., and A. Trihopoulou (2005). "Female Entrepreneurs' Personal Characteristics

and Motivation: A Review of the Greek Situation," Women in Management Review Vol.20(1), Pp.24-36.


Shane, S, L Kolvereid, and Westhead, P. (1991). "An Exploratory Examination of the

Reasons Leading to New Firm Formation across Country and Gender". Journal of Business Venturing, Vol. 6, 431-446.


Scheinberg, S. and MacMillan, I. (1988). “An Eleven-country Study of the Motivation to

Start a Business”. In B. Kirchoff, W. Long, W. McMullan, K. Vesper & W. Wetzel (Eds.), Frontiers of Entrepreneurship Research. Wellesley, MA: Babson College.


Scott, C. E. (1986). "Why More Women Are Becoming Entrepreneurs," Journal of Small

Business Management Vol. 24(4), Pp.37-45.
Selltiz, C.; Wrightsman, L; and Cook, S. (1976). Research Methods in Social Relations.

3rd Ed. New York, Holt, Rinehart and Winston.


Singleton, R. A,; Straits, B. C. and Straits, M. M. (1993). Approaches to Social Research.

2nd Ed. New York: Oxford University Press.


Soetan, R. O. (1991). The Role of Informal Savings and Credit Societies in the Growth of

Female-owned Businesses in South West Nigeria. Funded by Ford Foundation. http/www/fordfordationcreditforgrowthoffemale-ownedbusinesses/org.
Steven, S. (Ed) (1951). Handbook of Experimental Psychology. New York: Wiley
Strauss, A. and Corbin, J. (1998). Basics of Qualitative Research: Techniques and

Procedures for Developing Grouded Theory. Thousand Oaks, CA: Sage Publications.
Tabachnick, B. and Fidel, (2001). Using Multivariate Statistics. 4th edition, Needham

Heights, MA: Allyn and Becon.


Timmons, J.A. (1978). "Characteristics and Role Demands of Entrepreneurship,"

American Journal of Small Business Vol.3, Pp5-17.
Zikmund, W. G. (1994). Business Research Methods, Florida: The Dryden Press.


CHAPTER FOUR
DATA PRESENTATION, ANALYSIS AND INTERPRETATION OF RESULTS
4.0 Introduction

The primary purpose of this study is to examine the different motivational patterns that exist among women entrepreneurs in SMEs across different industrial sectors in the Nigerian economy with regard to starting and developing their own businesses. The secondary purpose is to examine the relationship between motivation and the performance of women entrepreneurs, the challenges they face in their businesses, their type of business ownership and environmental factors. The findings of the hypotheses tested in this study are discussed

This chapter begins with the information on the survey results and the description of the respondents' demographic information. The descriptive analyses of the variables used in this study were also presented. This was followed closely by the testing of the hypotheses formulated for this study and presented in the order of the hypotheses. Each hypothesis focused on the variables of the research with (motivational patterns as independent variables and women entrepreneurs as dependent variable). The analysis of the hypotheses was carried out based on the statistical tools adopted. The researcher’s position in this study was clearly stated under result presentation and discussion. These views were within the theoretical framework of this study.

4.1 Survey Results

Survey Results of this study were analyzed using SPSS 12 (SPSS, Inc., 2003) statistical program. Frequency distributions mean and standard deviation were developed and based on the respondent’s responses for each item as regards to the demographic data, data on the business, challenges facing women entrepreneurs and other aspects relating to information on the research questions. The results of the survey are shown below.



4.2 Descriptive Analysis of Variables

This section presents the descriptive analysis of the variables used in this study. All the variables selected and tested as independent and dependent were described in the tables

below.

Entrepreneurial Sector and Types of religions

It was shown that majority of the businesses owned by women entrepreneurs are in the distribution as 127(30%) in agricultural, 122(29%) in trade, 118(28%) in service and 55(13%) in manufacturing sector The study also revealed that out of these, 259 (61%) are Christians and 157 (37%) are Moslems while 6 (2%) of the respondents do not belong to any religion, or cannot be associated with either Christian or Moslem.


Table 38: Descriptive Statistics of Entrepreneurs by Sectors and Religions n=422,




Sectors

Religions of the Respondents

Sectors

Frequency

Percentage (%)

Religions

Frequency

Percentage (%)

Agriculture

127

30

Islam

157

37.2

Manufacturing

55

13

Christianity

259

61.3

Trade

122

29

Others

6

1.5

Service

118

28










Total

422

100

Total

422

100

Source: Field Survey, 2007
Structure of Respondents’ Business

The structure of business covered by the survey of the study shows that 382(91%) are sole trade business, 27(6%) are partnership business, 3(0.7%) belong to the category of company while 10(2.4%) are under cooperative society.


Table 39: Descriptive Statistics of Entrepreneurs by Structure of their businesses.

Variations

Frequency n=422

Percentage (%)

Structure of Businesses







Sole ownership

382

91

Partnership

27

6

Joint Stock Company

3

0.7

Others eg. Cooperative Society etc.

10

2.4

Total

422

100

Source: Field Survey, 2007

Number of Dependant Relatives and Age of the Respondents

Looking at the number of dependents of the respondents, the survey revealed that 136(32.2%) have one dependant, 171(40.5%) have two dependants, 37 (8.7%) have three dependants, 34(8%) have 4 dependants while 44(10.6%) have five dependants and above. Majority of the women entrepreneurs, 174 (41.23%) interviewed were between the ages of 31-35. This was followed by the age range of 21-26 which is 155 (36.72%). It was observed that few of them are either too young between ages 15 and 20 (4.26%) or too old between the ages of 40 and above 75 (17.78%).


Table 40:Descriptive Statistics of Entrepreneurs by Number of Dependants and Age




No of dependants of the Respondents

Age of the Respondents

Variations

Frequency n=422

Percentage. (%)

Variable

Frequency n=422

Percentage (%)

No of dependants







Age







1

136

32.2

15-20

18

4.26

2

171

40.5

21-26

155

36.72

3

37

8.7

31-35

174

41.23

4

34

8.0

40-45

51

12.08

5 and above

44

10.6

46-above

24

5.71

Total

422

100.00

Total

422

100.00

Source: Field Survey, 2007
State of Origin and Ethnic Background of the Respondents

Table 41 revealed that 138(32.7%) of the women entrepreneurs under the study are from Lagos State, 134(31.7%) of them are from Ogun State and 150 (35.6%) of them are from Oyo State. The ethnic background of those surveyed was Yoruba 388 (92%), Ibo 22(5%), Hausa 10 (2.0%), and minority 2(0.5%).


Table 41: Descriptive Statistics of Entrepreneurs by Tribe and State of Origin




State of Origin of the Resp.

Tribe of the Respondents

Variations

Freq n=422

Per. (%)

Variations

Freq n=422

Per. (%)

State of origin







Tribe







Lagos

138

32.7

Yoruba

388

92.5

Ogun

134

31.7

Ibo

22

5.0

Oyo

150

35.6

Hausa

10

2.0










Minority

2

0.5

Total

422

100.00

Total

422

100.00

Source: Field Survey, 2007

Age of Starting the Business and Educational Background

Table 42 was designed to capture the statistics on age of establishment and educational background of the respondents. Few of the respondents 18(4%) were at the age range of 15-20 when they started business, 155(37 %) were at the age range of 21-26 when they started their business, 174 (41%) were at the age range of 31-35 when they started their business while 51(12%) were between the age of 40 and 45 when their business started while 24(6%) of them were 46 old and above when they started their business. Considering the respondents educational qualification, majority of them 344 (82%) have WASE, 54(13%) of them are with OND certificates, 15 (4%) are with HND/BSc certificates while only 4 (1%) obtained MSc status in their certification and only 2(0.5%) have other certificates which was not actually specified.



Table 42: Descriptive Statistics of Entrepreneurs by Education and the Age they Started Business




Age of Business

Education Background of the Respondents

Variables

Freq n=422

Per (%)

Variables

Freq n=422

Per. (%)

Age of Starting Business







Highest education qualification







15-20

18

4

WASE

344

82

21-26

155

37

OND

54

13

31-35

174

41

HND/BSc

15

4

40-45

51

12

MSc

4

1

46-above

24

6

Others

2

0.5

Total

422

100

Total

422

100

Source: Field Survey, 2007
Marital Status and Number of Children of the Respondents

Out of the 422 respondents, it was observed that 263 (62%) were married while 146 (35%) are still single, 7 (3%) of them are divorced while 6(2%) of them are widow. Two hundred and two or 48% of them have two children, 102 (24 %) of them have three children, 48 (11%) had 4 children while 24 (6%) of them have five dependants and above.



Table 43: Descriptive Statistics of Entrepreneurs by Marital Status and Number of Children

Variations

Freq n=422

Per. (%)

Variations

Freq n=422

Per (%)

Marital Status







Number of Children







Single

146

35

1

46

11

Married

263

62

2

202

48

Divorced

7

3

3

102

24

Widow

6

2

4

48

11










5 and above

24

6

Total

422

100

Total

422

100

Source: Field Survey, 2007

Length of Work Experience and when the Business was Started

The majority of the women entrepreneurs surveyed had prior experience in their fields of endeavour. For example, out of the 422 women entrepreneurs, 10(2.4%) of the respondents had less than one year working experience, 48 (11.3%) of the respondents has one year working experience, 202 (47.8%) of them worked two years, 136 (32.2%) had working experience of three years, while 20(4.7%) and 6(1.6%) had a working experience of between four and five years respectively before they started their business. In other words, out of the women that owned business, more than half of them had related prior experience in their kind of trade. The survey also revealed that 20(4.74%) of the respondents established their business in less than one year ago, 130(30.80%) of the women under the study started their business in the last one year, 66 (15.64%) of them started their business in the last two years, 45 (10.66%) of them started their business in the last three years, 36 (8.53%) started their business in the last four years while 25 (29.6%) of them started their business in the last six years and above, 100 (23.70%) of them started their business in the last six years and above



Table 44: Descriptive Statistics of Respondents by Length of Work Experience and

when the Business was Started.

Variations

Freq n=422

Per. (%)

Variations

Freq n=422

Per (%)

How many yrs did you work for someone?







Year business was established







Less than one yr

10

2.4

Less than one yr

20

4.74

One yr

48

11.3

One yr

130

30.80

Two yrs

202

47.8

Two

66

15.64

Three yrs

136

32.2

Three

45

10.66

Four yrs

20

4.7

Four

36

8.53

Five yrs

6

1.6

five yrs

25

5.92

Six yrs and above

-

-

Six yrs and above

100

23.70

Total

422

100

Total

422

100
1   ...   6   7   8   9   10   11   12   13   ...   18


The database is protected by copyright ©dentisty.org 2016
send message

    Main page