Proceedings of the 12th European Conference on Knowledge ...

Radwan Kharabsheh, Ihab Magableh and Sukina Sawadha
description <strong>of</strong> <strong>the</strong> study was provided and <strong>the</strong>n an appointment was sought with <strong>the</strong> managers in <strong>the</strong>
listed companies. A total <strong>of</strong> 116 useable questionnaires were collected.
The data was codified and entered into SPSS. The Cronbach Alphas were acceptable exceeding
<strong>the</strong> recommended value <strong>of</strong> 0.6 (Sekaran, 2003) as shown in table 1. With regards to <strong>the</strong> data
distribution, it was found that <strong>the</strong> Asymp. Sig. (2-tailed) values for each variable were above 0.05
indicating that <strong>the</strong> data are normally distributed.
KMPs was measured by 5 items developed by (Zack et. al. 2009; Islam et. al. 2008; Maponya, 2004;
Earl, 2003; OECD, 2002; Aurum et. al., 2007; Maponya, 2004; Kasim et. al., 2008; Bozbura, 2007).
OP was measured by 5 items developed by (Fugate et. al., 2009; Choi et. al., 2008; Choi and Lee,
2003; Barker and Sinkula, 1999; Canlantone et. al., 2002). The size <strong>of</strong> <strong>the</strong> company was measured by
number <strong>of</strong> employees (Ling et. al., 2007) and <strong>the</strong> firm's age was measured by <strong>the</strong> number <strong>of</strong> years <strong>of</strong>
operation (Yang, 2010).
Table 1: Descriptive and goodness <strong>of</strong> fit statistics
Measure Mean
Standard
deviation
Asymp.
Sig. (2tailed)
Crombach’s
alpha
KMPs (five dimensions) 3.36786 0.9459
Communication (six items) 3.4756 0.78858 0.253 0.8043
The ability to experiment and create new
knowledge (four items)
3.4009 0.71161 0.428 0.7201
Knowledge capturing and acquisition (five
items)
3.4207 0.8392 0.169 0.8049
Training and competences development
3.2303
(seven items)
0.83316 0.305 0.8487
Policies and strategies <strong>of</strong> knowledge
management (six items)
3.3118 0.82665 0.33 0.8349
Organizational
dimensions)
performance (five
3.3758 0.4617 0.158 0.8066
Financial performance (two items) 3.2931
New product success (six items) 3.3836
Customer satisfaction (three items) 3.1724
Competitive intensity (four items) 3.5884
Market share (two items) 3.3147
5. Multiple Regressions Analysis (MRA)
The estimation process consists <strong>of</strong> three stages. In <strong>the</strong> first stage, <strong>the</strong> impact <strong>of</strong> KMPs on OP was
estimated (H1). Also, <strong>the</strong> effect <strong>of</strong> <strong>the</strong> control variables: firm's size and firm's age on <strong>the</strong> relationship
between KMPs and OP was estimated. In order to get a better understanding <strong>of</strong> <strong>the</strong> impact <strong>of</strong> KMPs
on OP, in <strong>the</strong> second stage, <strong>the</strong> impact <strong>of</strong> each dimension <strong>of</strong> KMPs on OP was estimated (H2 to H6).
This will allow us to find practice has <strong>the</strong> highest impact on OP. Finally, <strong>the</strong> impact <strong>of</strong> KMPs on each
dimension <strong>of</strong> OP was estimated (H7 to H11).
5.1 Stage 1: hypo<strong>the</strong>sis H1
The dependent variable is OP and <strong>the</strong> independent variable is KMPs. The estimation results show a
positive and significant impact <strong>of</strong> KMPs on OP at 1% significance level (refer to table 2). Fur<strong>the</strong>r, <strong>the</strong>
two control variable: firm's age and firm's size were found to have significant effect on OP and
<strong>the</strong>refore were omitted.
Table .2: estimation results <strong>of</strong> <strong>the</strong> impact <strong>of</strong> KMPs on OP
Hypo<strong>the</strong>sis Structural Path R- square B- value Prob
H KMPs (+) OP 0.54 .298 0.000
510