alpha for intrinsic rewards index is 0.8228, for extrinsic rewards index is
0.7197 and for employee satisfaction index is 0.856, a high Cronbach alpha for
both intrinsic, extrinsic rewards and motivation index confirms reliability of
has been conducted to reduce large amount of questions into few variables, it
is a tool that helps analysing correlations amongst variables by selecting set
of variables which are highly correlated, also known as factors (Minitab,
2017). Based on data collected it is important to focus on factors which can be
relevant for further research, therefore important factors which have high
loadings have been extracted using factor analysis given below in table 2.
Experimental studies from
(Wieringa el al, 2009) suggest that factor analysis can be conducted with
sample sizes below 50, this study is also in agreement with the theoretical
framework from (MacCallum et al,1999) which states that lower sample sizes less
than 12 are needed if the factor loadings are higher than 0.9 , even with high
number of factors . A lager number of variables greater than 12 are required when factor loadings are between 0.7 and 0.8.
For this research sample size of 36 is considered sufficient to conduct factor
analysis which helps in summarizing data that further helps in interpreting ,understanding
patterns as well as relationships. Factor analysis using varimax rotation and
maximum likelihood method is used, detailed results of Minitab session window
are given appendix 1 . The factors with high loadings are given below in table
2, the extracted factors can be used in future surveys by Human resources
statements: Why do you do your work?
1. Satisfaction experience after being
successful at a difficult task
2. I derive pleasure form learning new things
3. Satisfaction by taking interesting challenges
statements : Which rewards motivate you?
4. Receiving recognition by peers
5. Receiving verbal praise/ Appreciation
6. Challenging new assignments