Chapter one introduction 1 Background to the Study



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Source: Field Survey, 2007

Table 70 indicates that there is mutual correlation between the variables with a statistical significance. Among all the results, the strongest correlation is between competitiveness and support services (r=.362). This indicates that women entrepreneurial competitiveness can easily be enhanced through the activities of business support services. The result stood out among others showing a more positive correlation than the rest. Second to this was competitiveness and government policy(r=.277); followed by creativity/innovation and business support services (r=.261) and finally self-confidence and financing accessibility (r=.234).



Summary of the Results

The summary of the findings of the study are hereby presented below;



  1. The result from the testing of Hypothesis one revealed a significant difference at F (3, 419) =21.958, and p<0.015 at 3 degree of freedom and 0.05 significant level.The result of coefficient correlation revealed that a positive correlation exists between the motivational patterns and SMEs sub-sectors except family influence as a factor which showed a very low significant relationship with agricultural sector at r=0.18. Thus, the null Hypothesis one is rejected. This implies that different motivational patterns do exist among women entrepreneurs across different industrial sectors of the South-West Nigeria.

  2. The result obtained from the testing of Hypothesis two revealed that there is a positive relationship between motivational factors of women entrepreneurs and their performance in business. The magnitude of the correlation indicates how strong the relationship that exists between variables is. Factors that motivate Nigerian women entrepreneurs are clearly associated with performance in SMEs sub- sectors as indicated in the table. The magnitude of this correlation is r=0.12, 0.66, 0.74 and 0.61 for family influence, psychological, financial and environmental factors respectively.

  3. The result from the testing of Hypothesis three showed that the factors that motivated Nigerian entrepreneurs (family influence, psychological, financial and environmental factors ) and the challenges they face in business exhibit moderate positive values with family factor having the highest influence of 0.55, followed by environmental factors (0.42), psychological and financial factors with values 0.39 and 0.52 respectively. The null hypothesis which stated that “motivational factors do not determine the type of challenges women entrepreneurs face in business” was rejected and alternative hypothesis retained. The finding implies that motivational factors have significant effect in the determination of challenges women entrepreneurs face in business.

  4. The coefficient result revealed that there is a positive relationship between factors that motivate women entrepreneurs and their type of business ownership. The strongest influence is the environmental factors with the value of 0.77. This was followed by family influence with the value of 0.64, then psychological and financial factors with the values of 0.55 and 0.54 respectively. The highest value of the environmental factor confirmed the results in table 61 and 62 where majority of the respondents see competition as their major challenge in business. The null hypothesis which stated that “motivational factors do not determine women entrepreneurs’ type of business ownership” was rejected and alternative hypothesis retained. The finding implies that motivational factors have significant effect in the determination of women entrepreneurs’ choice of business ownership.

(v) The coefficient for this study reveals a significant relationship with values of 0.52, 0.42, 0.60 and 0.39 for access to finance, family and community support, support services and government policy (environmental factors) respectively with the factors that motivate women entrepreneurs. The result in Table 69 showed that all the environmental factors have positive relationship with the women entrepreneurial motivation. The null hypothesis which states that there is no relationship between environmental factors and women entrepreneurial motivation was rejected and the alternative hypothesis was accepted. This implies that there is relationship between environmental factors and women entrepreneurial motivation.


Table 71: Summary of the Findings from the Hypotheses Formulated

Title: Motivational Patterns of Women Entrepreneurs in SMEs: A Case Study in the South West Nigeria

Hypothesis

Variables

Statistical Tool

Findings

Literature Indication

Different motivational patterns do not exist among women entrepreneurs across different industrial sectors of the South-West Nigeria.

Variables such as risk taking, pursuit of moderate goals, tolerance of ambiguity,creativity and innovation, self-confidence, self-achievement, gender discrimination, social recognition, desire for extra income, freedom and independence were used in measuring motivational factors.

Analysis of Variance (ANOVA) and Coefficient correlation (which measures the relationship between variables) were used in testing hypotheses one.

The result from the testing of Hypothesis one revealed a significant difference at F (3, 419) =21.958, and p<0.015. The result of this correlation coefficient revealed that positive relationship exist between different motivational patterns and different industrial sectors in the South-west Nigeria.

Literature such as Scott (1986); Fisher, Reuber and Dyke (1993); Bartol and Martin (1998); Gracle (1998); Parboteeach, (2000); Hisrich, Micheal and Shepherd, (2005), Mansor, (2005); Brunstein and Maier (2005) suggested motivational factors such as difficult conditions at place of work, role model, desire for change of life style, ‘glass ceiling’, death of spouse, divorce and desire for extra income for women entrepreneurs.

There is no

significant

relationship

between


the factors that

motivate

Nigerian

women


entrepreneurs

and their

performance in

SMEs sub-

Sectors.


Variables such as sales volume, business profitability, market, products quality, personal income, business revenue, business assets, investment in equipment, no. of employees were used in measuring performance

Chi-square and Coefficient correlation were used to test the relationship between women motivational factors and their performance in business

The result obtained from the testing of Hypothesis two revealed that there is a positive relationship between women motivational factors and their performance in business. The magnitude of this correlation is r=0.12, 0.66, 0.74 and 0.61 for family influence, psychological, financial and environmental factors respectively. The Pearson Correlation also revealed that X2 calculated = 82.626 which is higher than X2 tabulated.

Women entrepreneurs’ motivational factors determine their performance in their businesses. This was in support of these works; Stoner and Fry (1982); Buttner and Moore (1997); Yves et al, (2001) and Akeredolu-Ale (1975). Others authors whom the result of this work supported their work include; Shapero and Sokol (1982); Kent, Sexton and Vasper (1982); Hisrich and Brush (1986) Aldrich and Zimmer (1986); Carsrud, Gaglio and Olm (1987).

Motivational

factors do not

determine the

challenges

women

entrepreneur



s

face in


business

Variables used in measuring challenges women entrepreneurs face in business include; combining family responsibilities, lack of access to finance, lack of support from spouse, customers’ complaints, sexual harassment, lack of power supply, gender discrimination etc

Coefficient correlation was used in testing hypotheses three. The Pearson Product-Moment Correlation Coefficient (r) measures the degree of linear relationship between two variables (independent and dependent).

The result from the testing of Hypothesis three showed that the factors that motivated Nigerian entrepreneurs and the challenges they face in business exhibit moderate positive values with family factor having the highest influence of 0.55, followed by environmental factors (0.42), psychological and financial factors with values 0.39 and 0.52 respectively. The highest point from family influence revealed that majority of the respondents were married and probalbily were having family problem.


Women entrepreneurs’ motivational factors determine the challenges they face in business. Literature such as Kickul, Welsch and Gundry (2001); Kuratko and Hodgetts (1995); Kutanis and Bayraktarogh (2003) argued strongly in support of this. The result of this work also supported the findings of Soetan, (1991); Finnegan and Danielsen (1997); Finnegan and Danilsen (1997); Dhaliwal (2000); Ryan and Deci (2002); Barwa (2003); Ogundele and Opeifa (2003) and Gelin (2005).

Motivational factors do not determine women entrepreneurs’ type of business ownership

Variables used in measuring choice of business ownership include; achievement of self-independence, involvement in family decision making, government support, low capital requirement, convenience, low risk involvement, improvement in quality of life.

Coefficient correlation was used in testing hypothesis four. The Pearson Product-Moment Correlation Coefficient (r) measures the degree of linear relationship between two variables (independent and dependent).

The coefficient result revealed that there positive relationship between factors that motivate women entrepreneurs and their type of business ownership. The coefficient result revealed that the strongest influence is the environmental factors with the value of 0.77. This was followed by family influence with the value of 0.64, then psychological and financial factors with the values of 0.55 and 0.54 respectively. Competition was chose in Table 61 and 62 as one of the major challenges facing the women entrepreneurs under this study.

Women entrepreneurs’ motivational factors determine the type of their business ownership Phizacklea (1990); Ram (1992); Ram and Jones (1998). Allen and Truman (1988); Brush (1992), Carter and Evans-Jones (2000) argued that ‘push’ factors are more likely to be identified with women entrepreneurs in Street Based Business’ (SBB), ‘Home Based Business’ (HBB) or Corridor Based Business’ (CBB). While ‘pull’ factors are more likely to be identify with women in medium and large enterprises.

There is no

significant

relationship

between the

environmental

factors and

women

entrepreneurial



motivation.


Enviromental factorsmay include accessibility to finance, labour, market, customers, suppliers, transport, and supporting service

Coefficient correlation was used in testing hypothesis five. The Pearson Product-Moment Correlation Coefficient (r) measures the degree of linear relationship between two variables (independent and dependent).

The coefficient for this study reveals a significant relationship with values of 0.52, 0.42, 0.60 and 0.39 for access to finance, family and community support, support services and government policy (environmental factors) respectively with the factors that motivate women entrepreneurs. The highest value of 0.60 indicated that there are some of the government policies that are not favourable to women entrepreneurs under this study. And second higest point on the family as a variable is an induication that a lot of them were in family-related business.

Literature such as Morris and Lewis (1991); Mansor (2005) and Familoni (2007) argued that entrepreneurial traits can be influenced by someone’s environment either negatively or positively. Environmental factors such as availability of infrastructures, training programmes, availability of finance and family support (ILO 2003). The findings however, contradicted the views of Stevenson (1986); Zellner, (1994); Greenberger and Sexton (1988); Taylor and Kosarek (1995) on this regard.

Source: Field Survey, 2007

The above table shows the summary of the findings from the hypotheses formulated in chapter one and test in chapter four of this study. The following are presented in the table: (i) the hypotheses formulated in chapter one of the study; (ii) the independented variables used in measuring the hypotheses; (iii) the inferential statistical tools used in testing the hypotheses; (iv) the findings from the tested in chapter four and (v) the literature indication of each of the findings. The table is expected to act as a guide and blue print to the entire work.



4.5 Women Entrepreneurial Motivation and Environmental Concentration

To examine the extent of women industrial concentration in the environment of the states of this study, Lorenz curve is employed. Lorenz curve is a graphic method of studying dispersion or otherwise of wealth or income distribution.


Table 72: Distribution of Responses According to States

Frequency Distribution

Lagos

Ogun

Oyo

0-4

11

9

20

5-9

4

6

9

10-14

2

2

2

15-19

2

2

1

20-24

1

1

0

25-29

0

1

0

Total

20

21

32

Source: Field Survey, 2007
Table 73: CALCULATION FOR DRAWING THE LORENZ CURVE










Lagos (A)

Ogun (B)

Oyo (C)

Median of group

Cum

Relative

Cum (%)

No

Cum

Relative Cum

(%)

No

Cum

Relative

Cum (%)

No

Cum

Relative

Cum(%)

2

2

2.3

11

11

55

9

9

42.9

20

20

62.5

7

9

10.3

4

15

75

6

15

71.4

9

29

90.6

12

21

24.1

2

17

85

2

17

80.1

2

31

90.9

17

38

43.7

2

19

95

2

19

90.5

1

32

100

22

60

69.0

1

20

100

1

20

95

0

32

100

27

87

100

0

20

100

1

21

100

0

32

100

Source: Field Survey, 2007

Interpretation

From the graph in the appendix, it can be seen that among the three curves (A, B and C) the Ogun State curve (A) is the closest to the straight line or line of equal distribution, followed by the Lagos State curve (B) then the Oyo State curve (C). The farther the curve to the diagonal line, the greater the inequality of concentration of the enterprises in their areas of location. Among the three curves, C which represents Oyo State is the farthest from the diagonal line. This shows that curve A and B are more concentrated than curve C. This means that women entrepreneurs are more concentrated in Ogun State, Lagos state than in Oyo State. See appendix three (3) in page 336 for the graph that shows the Lorenz Curve for the concentration and diversification of the enterprises in Lagos, Oyo and Ogun States.



4.6 Content Analysis

Apart from the descriptive and hypothesis analysis, this study was analyzed using content analysis (Holsti, 1969). Content analysis entailed open coding (line by line examination) and axial coding (identification of emergent patterns) of narrative data as delineated by Strauss and Corbin (1998). The respondents were asked to express their opinions on open-ended questions such as (i) what are the challenges, since you started this business? (ii) How do you think these challenges will be solved? (iii) What are the five main things that motivated you into business (iv) What are you advices to Nigerian women entrepreneurs?. The findings of the content analyses are shown below.


Table 74 shows the results of the open-ended questions that was addressed to the respondents which focused on the major challenges they face in business. In responding to the question, Table 74 shows that majority of the women 190 (22.28) responded that financial problem and lack of capital was the major challenge they face in business, this was followed by lack of electricity/infrastructural problem 119 (14.58%), customers dissatisfaction/complaints which 77 (9.43%)and lack of government support 69 (8.49%), untrustworthy personnel 62 (7.60%), unconducive business environment 53 (6.50%), high degree of competition 51 (6.25%) and lack of managerial skills 50 (6.12%).

Table 74: Respondents’ Major Challenges in Business

Statement

Frequency

Percentage (%)

Financial problem and lack of capital

190

22.28

Location and high tenancy rate

40

4.90

Unconducive business environment

53

6.49

Government policy and support

69

8.48

Lack of resources, labour, material and time

31

3.79

Lack of managerial skills and competence

50

6.12

Lack of trust worthy personnel

62

7.59

Lack of electricity /infrastructural problem

119

14.58

Customers dissatisfaction and complaints

77

9.43

High degree of competition

51

6.25

Nature of business/lack of diversification

16

1.96

Lack of training and development/inexperience

25

3.06

Lack of family support

26

3.23

Lack of access to Information technology

8

0.98

Sexual harassment

3

0.86

Total

816

100

Source: Field Survey, 2007
These responses confirmed the result of this study from the interview conducted with thirty six (36) women entrepreneurs which focused on finding out the major challenges they face in business. Out of the 36 women entrepreneurs, 85% of them responded that finance was the major challenge they were facing in business, 64% mentioned power as their major challenge, 56% said that customers dissatisfaction and compliants was their major challenge, 51% need Government intervention, 49% said that competition in their business was so high while 42% regretted not having much experience before going into the business and this was a problem to them. Below is a response given by one of the women interviewed;

Since I started this business 6years ago, the major challenges I face is finance and how to raise capital to run my business. Again in my area, we hardly see light, since our transformer spoiled five months ago, nobody is asking us anything and it has been so terrible. As a result, my customers decided to go somewhere else when they discovered that I could not afford generator to cool my drinks. Apart from that, the business I’m into is men’s business and I did not anticipate that I had to compete with men as my competitors. Again, my going into business was a sudden one. “I never took out time to meditate on the challenges facing other women entrepreneurs before going into this business”. I will say I lack managerial skills required for the success of this type of business (35years old woman involved in the sale of drinks at Ikeja, Lagos).


Table 75 shows the responses of the respondents with regards to the question “how do you think the challenges will be solved?” Out of the total number of 605 responses, financial assistance/provision of loan has the highest point of 137 (22.64%). This was followed by six others items which include having good government policy/governance 108 (17.86%), provision of electricity/infrastructure 94(15.53), meeting customers’ satisfaction 38 (6.28%), motivation of staff 49(8.10%), adoption of new management approach/customer responsibility 33(5.46%) and training and development 32 (5.28%).

Table 75: Respondents’ Opinion on How to Solve Specific Challenges

Statement

Freq.

Per. (%)

More efforts to develop managerial skills

21

3.47

Involvement in advertisement

20

3.30

Financial assistance/loan

137

22.64

Motivation of staff

49

8.10

Good government policy/ governance

108

17.86

Meeting customer satisfaction/ high product quality/price

38

6.28

New management approach/customer responsibility

33

5.46

Access to information technology

12

1.98

Networking/co-operative society

10

1.66

Training/development

32

5.28

Family support

30

4.96

Supply of electricity/infrastructure

44

7.27

Availability of infrastructure

50

8.26

Self motivation/determination

21

3.47

Total

605

100

Source: Field Survey, 2007

The response from the above table confirmed the result of the interview conducted with some (36) of the respondents. 89% of them were of the opinion that if only they will be given access to loan and micro credit that will help them out, 74% of them said that government need to change some of their policies and the way they do things, 69% of them were of the view that if they have constant power supply, that will help in satisfying their customers, 62% of them need training and seminar to be equipped with required skills while 51% of them wanted to know how to stop high rate of labour turnover. This, according to them will help a great deal. Here is the response from one of the respondents:

I believe there is a way out of every problem. Our people usually say that where there is a will there is a way. I feel if the government will give me small loan and capital for doing the business, I think it will help out. Also the government must give us light because it is one of the things that is giving us headache. We also need to be trained for us to know how to do business well. I think if all these are taken care of, our business go better (40 years old woman in food selling business in Sango, Ogun State).

Table 76 shows the responses to the question on “what motivated you into business” Out of the 548 responses from the respondents, 112 (20.44%) agreed that they entered into business because they attended women empowerment programme which motivated them to start their business, 84 (15.33%) of them accepted that they went into business because they needed extra financial assistance, 74 (13.50%) agreed that they were self motivated, 65 (11.86%) went into business through their friends’ advice and creating of awareness, 64 (11.68%) agreed that the government organized a training through NDE and SMEDAN, this helped them to get started, 50 (9.12%) saw their family as a motivator for their going into business.



Table 76: Respondents’ Entrepreneurial Motivation

Statement

Freq.

Per. (%)

More enlightment /creating of awareness

65

11.86

Ensuring of gender equality

37

6.75

Financial assistance

84

15.33

Women empowerment programme

112

20.44

Government involvement through good policy

64

11.68

Self motivation

74

13.50

Availability of infrastructural facility

10

1.82

Confidence/competitiveness

19

3.47

Elimination of cultural/religious barriers

3

0.56

Handling of environmental hazard e.g sexual harassment

13

2.37

Family support

50

9.12

Involvement of women in networking

13

2.37

Availability of information technology

4

0.73

Total

548

100

Source: Field Survey, 2007

Below is a report from one of the respondents in the interview we conducted;



My going into business I will say, was motivated as a result of a programme I attended in my church. There they encouraged us to start up a business immediately with any small money in our hand. Again, I was really pushed to start the business when I discovered that I needed extra money to support my husband. Even though my husband initially was not in support of the idea of me going into business, I encouraged myself because I know what I am looking for. Initially, capital was a problem but one of my brothers- in-law loaned me N20,000, that was seven years ago. This really helped out (37 years old pure water producer at Ibadan Central, Oyo State).
Table 77 revealed the result of the advice offered by the respondents to Nigerian women entrepreneurs. Seventy two or 16.33% of the respondents suggested that self-determination is the best way Nigerian women should be encouraged into business, 61 (13.83%) advised the Nigerian women to work harder, 48 (10.88%) of them advised them to be self motivated, 41 (9.30%) of them advised them to be more focused while 39 (8.84%) and 26 (5.90%) of them advised them to learn to be proactive and start small.
Table 77: Respondents’ Advices to Nigerian Women Entrepreneurs

Statement

Freq.

Per. (%)

Intrinsic / Extrinsic

Self motivation

48

10.88

Intrinsic motivation

Self determination

72

16.33

Intrinsic “ “

Self esteem

39

8.84

Intrinsic “ “

More education

13

2.95

Intrinsic “ “

Focused

41

9.30

Intrinsic “ “

Hard work /industry

61

13.83

Intrinsic “ “

Morality/Integrity

9

2.04

Intrinsic “ “

Mentorship

6

1.36

Extrinsic “ “

Self satisfaction

8

1.81

Intrinsic “ “

Financial prudence

14

3.17

Extrinsic “ “

Networking

15

3.40

Extrinsic “ “

Seeking for family support

19

4.31

Extrinsic “ “

Confidence/boldness

24

5.44

Intrinsic “ “

Training/development

23

5.22

Intrinsic “ “

Learn to attract/retain staff

10

2.27

Intrinsic “ “

Start small

26

5.90

Extrinsic “ “

Customer satisfaction

3

0.68

Extrinsic “ “

Risk taking

10

2.27

Intrinsic “ “

Total

441

100




Source: Field Survey, 2007
The responses in Table 77 were further classified into intrinsic and extrinsic motivation. The result shows that, out of the nineteen (19) points, thirteen (13) are classified under intrinsic motivation while six (6) are extrinsic motivation.

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