Challenges in the Era of Globalization - iaabd

Proceedings of the 12th Annual Conference © 2011 IAABD
questionnaire, either deliberately or in error. For either case, this creates missing values that are items to
which no response was provided. Missing values must be identified and managed or else they affect
multivariate analysis (Field, 2006; Hair, et al., 1998).We examined the pattern of the missing values and a
few (05) cases that had a large range of missing values were discarded. While cases that had a narrow
range (< 5%) of missing values which were completely at random, such values were replaced using the
series mean. The series mean was adopted because it provides the best estimate of the missing value
otherwise the cases would be vulnerable for either pair wise deletion or list wise deletion which could
further reduce the magnitude of the data (Field, 2006; Hair, et al., 1998). After the analysis of missing
values, where five (05) cases were dropped, the researchers retained 237 cases that represented 51
parastatal organizations. We screened the data for outliers following Field’s (2006) guidelines.
We used exploratory factor analysis (EFA) in order to identify the most important organizational
resilience factors. We conducted the factor analysis based on 237 observations which were large enough
to warrant factor analysis. The Kaiser-Meyer-Olkin (KMO) and Barttlet’s Sphericity tests which
determine the sampling adequacy and significance of correlations, respectively, were used as initial
considerations for the factorability of the variables (Field, 2006). The KMO was above 0.7 to warrant
sample adequacy and the Barttlet’s Sphericity test was significant (see table 2 below), suggesting that
there were significant correlations among the variables for factor analysis to be carried out. After
determining the adequacy of the data for factor extraction, we then conducted for each variable; a
principal component analysis which is recommended for extraction at the eigen value of greater than 1
without fixing the number of factors to be extracted because we were exploring the construct validity, and
a varimax factor rotation which assumes independence of factors and is parsimonious (Field, 2006; Hair,
et al., 1998). The researchers set the minimum factor loading of .5 which was high enough to extract the
most significant items to load on the extracted factors (Field, 2006; Hair, et al., 1998).
From the above analysis, factor structures for the study variables were examined, then the extracted
components were labeled based on the majority of items that loaded on each component and the extant
literature and theory (Field, 2006; Hair, et al.,1998). The researchers noted that some of the items loaded
on different components contrary to where they previously constructed which is normal in exploratory
factor analysis. There were also some cross loadings and the researchers took the higher loading after
evaluating their contribution theoretically. The cumulative percentage of the variance explained by the
components based on the rotation sums of squared loadings were above the minimum of 60% (Hair, et al.,
1998).
Results
Table 1: Descriptive Statistics (n=237)
Organisational Resil.
Organisational Adapt
No. of
items
18
6
M (SD) Skewness
(SE=
.333)
3.36 (.38)
3.62 (.57)
-.17
-.86
Kurtosis
(SE=
.656)
-.54
Organizational Compt 6 3.48 (.49) .39 .05 .78
Organisational Value 6 2.98 (.67) .26 -.53 .63
.63
Alpha
.89
.80
412