4.1 Demographic Details of the Respondents:
Following is a table that lists the demographic information of the selected entrepreneurs, including gender, education level and occupation. The data was analysed using descriptive statistics.
Table 1: Demographic information about the respondents (N=230)
Measures
|
Items
|
Frequency
|
Percentage
|
Gender
|
Male
|
156
|
62.8
|
Female
|
74
|
37.2
|
Age
|
Below 24
|
13
|
5.5
|
25-30
|
36
|
15.5
|
30-35
|
48
|
20.9
|
35-40
|
73
|
31.7
|
40 & above
|
60
|
26.3
|
Education
|
Secondary
|
4
|
1.6
|
Undergraduate
|
25
|
10.5
|
Postgraduate
|
197
|
85.2
|
Others
|
4
|
1.6
|
Occupation
|
Business
|
145
|
63.04
|
Salaried
|
56
|
24.34
|
Others
|
29
|
12.6
|
Type of business
|
Micro
|
65
|
28.2
|
Small
|
82
|
35.6
|
Medium
|
83
|
36.08
|
Activities of business
|
Manufacturing
|
98
|
42.6
|
Transport
|
12
|
5.21
|
Construction
|
29
|
12.6
|
Trade & commerce
|
56
|
24.34
|
Restaurants
|
9
|
3.91
|
Service
|
19
|
8.26
|
Others
|
7
|
3.04
|
4.2 Descriptive statistics of all the variables: It indicates that mean of the variables observed from 3.56 to 4.53. The skewness and kurtosis values for the data is between -2 to +2 and standard deviations are above 0.5. All these facts confirm that the data is normally distributed for analysis using a structural equation model.
Table 2 Descriptive statistics:
Variables
|
Mean
|
Standard deviations
|
Skewness
|
Kurtosis
|
IF1
|
4.53
|
.763
|
-1.889
|
1.773
|
IF2
|
4.38
|
.837
|
-1.315
|
1.057
|
IF3
|
4.41
|
.824
|
-1.545
|
2.085
|
IF4
|
4.52
|
.824
|
-2.112
|
2.101
|
IF5
|
4.36
|
.913
|
-1.532
|
2.024
|
BSF1
|
4.39
|
.859
|
-1.559
|
2.291
|
BSF2
|
4.40
|
.874
|
-1.576
|
2.105
|
BSF3
|
4.41
|
.835
|
-1.536
|
2.085
|
MF1
|
4.13
|
.879
|
-.851
|
0.241
|
MF2
|
4.21
|
.888
|
-1.225
|
1.512
|
MF3
|
4.39
|
.879
|
-1.671
|
2.059
|
MF4
|
4.33
|
.933
|
-1.595
|
1.700
|
BEF1
|
4.38
|
.799
|
-1.422
|
2.085
|
BEF2
|
4.40
|
.775
|
-1.411
|
2.075
|
BEF3
|
4.47
|
.829
|
-1.773
|
2.184
|
BEF4
|
4.46
|
.818
|
-1.710
|
2.012
|
SCF1
|
3.65
|
.731
|
-2.153
|
2.076
|
SCF2
|
4.20
|
.768
|
-1.466
|
2.149
|
SCF3
|
3.56
|
.811
|
-2.053
|
1.721
|
SCF4
|
3.84
|
.768
|
-1.985
|
2.206
|
S1
|
4.47
|
.728
|
-1.622
|
1.332
|
S2
|
4.43
|
.679
|
-2.171
|
2.016
|
S3
|
4.38
|
.693
|
-1.849
|
2.77
|
4.3 Factor analysis:
The study used factor analysis before conducting any analysis. The factor analysis help in determining different successful factors of entrepreneurs. The study selected principal component analysis using Promax for factor extraction. The various results obtained from factor analysis such as the Kaiser–Meyer–Olkin (KMO) test of sample adequacy statistic is 0.922, which indicate sample is good enough for further analysis. The significant value of Bartlett test of sphericity also supports the adequacy at the 1% level of significance.
Finally, the factor extraction based on Eigen value above 1 and Scree plots above elbow point’s value revealed the six factors were finalized for the study explaining the total variance of 78.53%, with factor loading of each item above 0.7.
The internal consistency for the proposed scale items were calculated using Cronbach’s alpha value of reliability. The values for the study items are shown in the table 2. It can be inferred form the table that alpha values ranging from 0.815 to 0.914 and all these values are above the threshold value of 0.70. (Hair et al., 2010).
Table 2 KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling.
|
.922
|
Bartlett's Test of Sphericity
|
Approx. Chi-Square
|
4476.406
|
Df
|
253
|
Sig.
|
.000
|
Source: Primary survey
Table 3: Scale Items and Factor Loadings
|
Scale Items
|
Factor Loadings
|
Cronbach's alpha
|
|
Individual factors (IF)
|
IF1
|
I am confident to perform good in this business
|
.789
|
0.878
|
IF2
|
I am very innovative and creative in my actions
|
.780
|
IF3
|
I always try hard to improve my performance
|
.769
|
IF4
|
I am a risk seeker and good at handling failures
|
.729
|
IF5
|
Experience and business skills
|
.789
|
|
Business support factors (BSF)
|
BSF1
|
Financial support
|
.903
|
0.914
|
BSF2
|
Government support
|
.897
|
BSF3
|
Family and friends support
|
.875
|
|
Management factors (MF)
|
MF1
|
Management commitment and support
|
.806
|
0.860
|
MF2
|
Human resource management practices
|
.781
|
MF3
|
Organizational culture
|
.738
|
MF4
|
Work environment and communications
|
.716
|
|
Business environment factors (BEF)
|
BEF1
|
Economic factors
|
.811
|
0.826
|
BEF2
|
Technological factors
|
.764
|
BEF3
|
Legal factors
|
.751
|
BEF4
|
Ecological factors
|
.734
|
|
Socio-cultural factors
|
|
0.815
|
SCF1
|
The support from close ties (spouse, parents, friends) has a positive effect on my business growth & success
|
.858
|
SCF2
|
The society’s attitude towards my products/services is positive
|
.842
|
|
SCF3
|
I have no cultural influences
|
.816
|
SCF4
|
The society views my involvement in business positively.
|
.713
|
|
|
Entrepreneur Success
|
S1
|
There is an increase in sales and profitability o
|
0.813
|
0.905
|
S2
|
The number of employees started to increase
|
0.785
|
S3
|
The reach of products increased in market and are having high market potential
|
0.712
|
Source: Primary survey
4.4 Confirmatory factor analysis (CFA) of measurement model of each latent variable.
The two major results of CFA i.e. Goodness of fit of the model prepared by considering each latent variable as exogenous variable and the reliability & validity of the CFA model.
The goodness of fit indices mentioned in table 4 indicate that model is fit with empirical data as all the indices values are under the threshold values.
The reliability and validity in table 5 mentioned that Composite reliability (CR) values used for internal consistency measurement of the data is above the threshold value of 0.7. The Average Variance Extracted (AVE) values greater than 0.5 confirm the composite validity of data. Further, all the Maximum shared variance (MSV) values are below AVE, confirmed the discriminant validity of the data. Thus, the data of the present study is reliable and valid for hypothesis testing.
Table 4: Goodness of Fit indices in CFA model
Indices
|
Abbreviation
|
Observed values
|
Recommended criteria
|
References
|
Normed chi square
|
χ2/DF
|
1.910
|
1<χ2/df<3
|
Hair et al., (2010)
|
Goodness-of-fit
|
GFI
|
.873
|
>0.90
|
Adjusted GFI
|
AGFI
|
.837
|
>0.80
|
Normed fit
|
NFI
|
.911
|
>0.90
|
Comparative fit
|
CFI
|
.955
|
>0.95
|
Root mean square error
|
RMESA
|
.063
|
<0.05 good fit
<0.08 acceptable fit
|
Tucker-Lewis’s index
|
TLI
|
.947
|
0<TLI<1
|
Source: Primary survey
Table 5: Reliability and validity
CR
|
AVE
|
MSV
|
IF
|
SCF
|
MF
|
BEF
|
S
|
BSF
|
|
IF
|
0.879
|
0.594
|
0.883
|
0.771
|
|
|
|
|
|
SCF
|
0.927
|
0.762
|
0.936
|
0.558***
|
0.873
|
|
|
|
|
MF
|
0.861
|
0.608
|
0.872
|
0.529***
|
0.646***
|
0.780
|
|
|
|
BEF
|
0.926
|
0.758
|
0.935
|
0.630***
|
0.590***
|
0.740***
|
0.871
|
|
|
S
|
0.908
|
0.766
|
0.910
|
0.633***
|
0.632***
|
0.674***
|
0.704***
|
0.875
|
|
BSF
|
0.953
|
0.871
|
0.956
|
0.434***
|
0.430***
|
0.485***
|
0.523***
|
0.600***
|
0.933
|
Note: Statistical significance (* p < 0.05, ** < 0.10, **** < 0.001) of the correlation
Convergent validity and reliability are met if CR > 0.7 (composite reliability) and AVE > 0.50 (convergent validity) (discriminant validity is met)
Source: "Master Validity Tool", AMOS Plugin, Gaskin, J. and Lim, J. (2016).
4.5 Structural equation Modelling (SEM) for hypothesis testing:
The structural model is series of regression lines drawn from predictors to outcome variables. For the present study, with given data the SEM model was tested for checking the impact of different factors such as internal, socio-cultural, management, business environment and business support on the success of MSMEs entrepreneurs.
The findings of the figure 3 and table 6 revealed the impact of each factor on dependent variable (success of entrepreneur). The standardized coefficient weights (β), critical ratios and p values are used for testing the hypotheses. It was mentioned that Factor 1 (Individual factors) had a significant influence on entrepreneur success (ß =0.202, CR = 2.875, p = 0.004) as the p value <0.05, thus hypothesis H1 was accepted.
The impact of socio-cultural factor is positive with regression weights value ß =0.173, CR =2.485, p =0.013, confirming the hypothesis H2.
Management factors are also having positive and significant impact on success of entrepreneurs ß =0.178, CR =2.010, p =0.044, hence hypothesis H3 was approved since critical ratio above 1.96 with p<0.05.
The business support factors are significantly influencing the success of entrepreneur with ß =0.237, CR =4.107, p = 0.00. Thus, hypothesis H4 was accepted as the p value<0.05. Finally, the business environment factors are also contributing in success of the entrepreneurs as ß =0.219, CR =2.505, p =0.012, confirming the hypothesis H5.
The findings of the study revealed that all the five factors selected in the study are able to explain 65% of total variance in success of the MSMEs entrepreneurs, remaining 35% variance is beyond the scope of present study.
Further, the goodness of fit indices of the structure model Chi-Square Value CMIN/DF = 2.146, GFI = 0.919, AGFI = 0.889, NFI = 0.929, CFI = 0.959, and RMSEA = 0.057 are under the threshold values confirming the good fit of model.
Table 6: Results of structural model:
Hypo.
No
|
Path
|
ß
|
CR
|
P value
|
Decision
|
H1
|
Individual factors à Success
|
.202
|
2.875
|
.004
|
Accepted
|
H2
|
Socio-cultural factors à Success
|
.173
|
2.485
|
.013
|
Accepted
|
H3
|
Management factors à Success
|
.178
|
2.010
|
.044
|
Accepted
|
H4
|
Business environment factors à Success
|
.219
|
2.505
|
.012
|
Accepted
|
H5
|
Business support factors à Success
|
.237
|
4.107
|
***
|
Accepted
|
Source: Primary survey