5 CHAPTER 5: DATA ANALYSIS

5.1 Introduction
–
5.2 Data analysis
The data analysis process of this research study relies on the findings of the survey and data
collected methods used in the study. The research analyzed the results of the primary data or
survey questionnaires using the statistical tools, SPSS and Likert scale. The survey questionnaire
consisted of the close-ended questions that restricted or limited the scope of the study. This
helped the researcher to obtain results focusing on the achievement of research objectives.
Saunders, Lewis and Thornhill (2007) stated that generally selects an appropriate analyzing
technique keeping in view the nature of the study under discussion. The researcher considered the
importance of the following factors for the analysis of the collected data.
• The research study used the reliable measuring instruments, the Cronbach alpha
coefficients.
• The measuring instrument provides the valid results, by constructing validity, including
the discriminating and converging validity. The Discriminant validity is a primary tool for the
calculation of construct validity for analysis.
• The researcher implemented the Exploratory Factor Analyses (EFA), for the collected data
for discovering the structure, most appropriate for the represented data. EFA is also beneficial
for assessing the value and importance of the individual items and their exploratory objectives.
• The researcher implemented the Structural Equation Modelling (SEM), because the statistical
techniques were applied for measuring the various variables affecting the causal relationships
among them, also influencing effectiveness of the organization. The SEM inspects the
interrelationships that can be articulated as the series of multiple regression equations. It also
provide the understanding of diverse patterns and their correlation among the set of different
variables and for describing their variance with respect to the defined model.
5.3 Characteristics of participants
All the participants of the survery were from the largest GCC telcom companies as described
eailer . A mail survey was conducted of all 1100 participant, but only 390 usable questionnaires
were returned and 35 questionnaires were deemed invalid. So, The response rate of about thirty-
five percent (35.45%). The participants were under no obligation to complete and return the
questionnaires. The confidentiality and anonymity of those who did return completed questionnaires
were guaranteed by them sending the questionnaires directly to the researcher in the prepaid
envelope

5.4 Reliability
In the present study, the Cronbach (1951) coefficient alpha was used to calculate the internal
consistency (reliability) of the measuring scales
Case Processing Summary
N %
Cases Valid 355 100.0
Excludeda 0 0.0
Total 355 100.0
a. Listwise deletion based on all variables in the procedure.
–
Cronbach’s Alpha N of Items
.918 68
Table ‎5 1 Reliability

5.5 Exploratory Factor Analysis (EFA)
In the present study, sufficient proof of content and criterion-related validity was established on
the basis of the literature review. In view of the importance of construct validity, it was
important to assess the discriminant validity of the measuring instruments. For this purpose three
sets of exploratory factor analyses were conducted
In the exploratory factor analyses, Principal Component Analysis was specified as the method of
factor extraction and Varimax rotation of the original factor matrix was used in all instances. The
factor analyzing of the Information Technology (IT) and Leadership, Shared Values and Strategic
management, Employees and business processes variables, the extraction of thirteen factors were
specified. After considering various factor solutions, it had to be concluded that the instruments
used to measure the IT processes did not demonstrate sufficient evidence of discriminant validity.
Ten, instead of thirteen, distinctly separate variables could be identified. The most
interpretable factor structures for ten variables are reported in Table ‎5 3(below).

Rotated Component Matrixa Component
H2:1,2 LS OS H3 : SV H4 SM ITA ITS ESM ITB H6 BP ESB
Reliability 0.845 0.845 0.818 0.778 0.712 0.725 0.641 0.611 0.712 0.55
LS5 .718
LS6 .700
LS1 .674
LS4 .624
LS2 .606
LS3 .590
LS8 .577
OE6 .752
OE5 .713
OE4 .707
OE3 .702
OE2 .690
OE1 .650
SV11 .803
SV52 .784
SV12 .737
SV51 .673
SV6 .540
SM1 .719
SM6 .668
SM2 .628
SM3 .607
SM7 .592
ITP5 .753
ITP2 .632
ITP4 .621
IT2 .731
IT5 .601
IT3 .599
ES6 .652
ES7 .640
ES2 .589
ES1 .506
ITP1 .652
IT4 .651
ITP3 .599
IT1 .592
BP2 .689
BP5 .658
BP1 .580
ES3 .764
ES8 .722
LS7 .605
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization. a
a. Rotation converged in 8 iterations.
Table ‎5 2 : EFA Rotated Matrix

Based on the preceding discussion on the factor analyses, it can be concluded that a new factor
structure has emerged for the Information technology implementation satisfaction (ITS) variables.
This factor structure demonstrates acceptable discriminant validity. The ten factors were thus
distinct and separate latent variables.
The Cronbach reliability coefficients of the instruments as they emerged from the factor analyses
were then re-calculated to confirm their internal consistency. Based on the factor analysis
results, certain latent variables were reconstructed or removed from the original theoretical
model. The reliability based on the new structure as mentioned in Table ‎5 3 (below). All the
Cronbach reliability coefficients were above the 0.500 cut-off point needed for basic research
(Tharenou, 1993; Pierce and Dunham, 1987).

latent variable LS OS SV SM ITA ITS ESM ITB H6 BP ESB
Cronbach reliability 0.845 0.845 0.818 0.778 0.712 0.725 0.641 0.611 0.712
0.55
Table ‎5 3: EFA- Reliability
Based on the exploratory factor analysis results Table ‎5 2 (above), variables had to be redefined.
For all subsequent analyses, the following variables were defined as follows:
5.5.1.1 Information Technology (IT)
IT Behavior:
H.b1: The Organization believes that the use of information technology has an impact On
Organizational Performance
H.b2: The Organization believes that the use of information technology has an impact on
Employees’ behavior in accordance with the company’s strategy
H.b3: The Organization believes that the use of information technology has an impact on Employees’
Motivation in accordance with the company’s strategy
IT Satisfaction
H.s1: To what extent the IT satisfaction has an impact on Employees’ behavior in accordance with
the company’s strategy
H.s2: To what extent the IT satisfaction has an impact on Employees’ motivation in accordance
with the company’s strategy

IT Implementation (ITA)

H.a1: The Organization applies the information technology has an impact Employees’ motivation in
accordance with the company’s strategy
H.a2: The Organization applies the information technology to improve the business processes in
accordance with the company’s strategy
H.a3: The Organization applies the information technology to improve the on organizational
effectiveness
5.5.1.2 Leadership (LS)
H2.1: The leadership style has an impact on organizational effectiveness.
H2.2: The leadership style has an impact on the Employees’ motivation.
H2.3: The leadership style has an impact on the business processes
5.5.1.3 Shared Values (SV)
H3.1: The organization develops and motivates shared value has an impact on organizational
effectiveness
H3.2: To what extent the Shared Value have an impact on the on the Employees’ behavior
H3.3: To what extent the Shared Value has an impact to improve the Business Process
5.5.1.4 Strategic Management (SM)
H4.1: To what extent the strategic management an affect the organizational effectiveness
H4.2: Strategic management improves the business processes in accordance with the company’s
strategy
H4.3: Strategic management influence on the Employees’ behavior

5.5.1.5 Employees (ES)
H5. 1 Employees’ behavior has an impact on the organizational effectiveness
H5. 2 Employees’ motivation has an impact on the organizational effectiveness
5.5.1.6 Business Processes (BP)
H6. 1 There exist association among the Processes of firms and organizational effectiveness.

5.6 The descriptive statistics after exploratory factor analysis

OS LS SV SM ITA ITS ITB ESM ESB BP
Disagree* 7% 5% 3% 5% 2% 4% 1% 2% 46% 12%
Neutral 42% 29% 13% 24% 12% 19% 10% 20% 21% 38%
Agree** 51% 66% 84% 71% 85% 77% 90% 78% 34% 49%
Table ‎5 4:Overall Respondents Statistics for all variables
*present (Both Disagree and strongly disagree) **present (Both agree and Strongly agree)
5.6.1 Information Technology

As mentioned in Table ‎5 4 (above), the overall participates believes that the information
technology has a positive impact in the organization performance and improve the business processes
and they are satisfied with the level of implementation.
5.6.1.1 IT Believes

Participates agreed with 90% that the believes of IT in the organization will positively impact
organization’s performance and Employees’ behavior
5.6.1.2 IT Satisfaction

Participates agreed with 77% that the employees satisfied with the level IT implementation in the
organization.
5.6.1.3 IT Implementation

Participates confirmed with 85% that the level IT implementation in the organization will
positively improve Employees’ motivation and Organization’s Business Process plus enhance
organizational effectiveness
5.6.2 Strategic Leadership (LS)
As mentioned in Table ‎5 4 (above), 66% from participates believed that the leadership style has a
positive impact on organizational effectiveness, as well as has a positive impact on the Employees’
motivation.
5.6.3 Shared Values (SV)
As mentioned in Table ‎5 4 (above), 84% compared to 3% from participates believed that develops and
motivates shared value has a positive impact on organizational effectiveness, as well as has a
positive impact on the Employees’ behavior and Business Process.
5.6.4 Strategic Management (SM)

As mentioned in Table ‎5 4 (above), 71% compared to 5% from participates confirmed that strategic
management has a positive impact on organizational effectiveness, as well as has a positive impact
on the Employees’ behavior and Business Process.
5.6.5 Employees (ES)

As mentioned in Table ‎5 4 (above), 46% compared to 34% from participates disagreed that Employees’
behavior is positively related with organizational effectiveness, this shows that there is a major
problem in how to deal with employees within the company
78% compared to 2% confirmed that Employees’ motivation has a positive impact on organizational
effectiveness
5.6.6 Business Processes (BP)
As mentioned in Table ‎5 4 (above), 49% compared to 12% from participates agreed that there exist
association among the Processes of firms and organizational effectiveness

All subsequent analyses were based on the revised hypothesized model shown in Figure ‎5 1
Figure ‎5 1 : Revised Model

5.7 CONFIRMATORY FACTOR ANALYSIS (CFA)
A Confirmatory Factor Analysis (CFA) was conducted by using the AMOS statistical software as shown
in Figure ‎5 2 . This analysis sought to establish further evidence of construct validity by
confirming the empirical factor structure that emerged from the exploratory factor analyses. The
goodness-of-fit indices of the CFA are shown in Table ‎5 5. The results show that CFA solution
provide further evidence of construct validity.
Sample Size 355
Chi-square 1074.818
Degrees of freedom 739
Probability level 000
Root mean square error of approximation (RMSEA) 0.036
Goodness-of-Fit Indices (GFI) 0.87
Table ‎5 5: Results of the Confirmatory Factor Analysis
The indices of fit depicted in Table ‎5 5 indicate acceptable levels of fit. An RMSEA value of
between zero (0) and 0.05 indicates a close fit, between 0.05 and 0.08 a reasonable fit, and above
0.08 a poor fit (MacCullum, Browne and Sugawara, 1996). The GFI is believed to be one of the best
absolute indices of model fit (Hoyle, 1995: 91). The GFI indicates the overall degree of fit of the
hypothesized model on the data. The higher the GFI value in the range from 0 to 1, the better the
goodness of fit. A GFI value of 0.90, for instance, represents a better fit than a value of 0.80.
Table ‎5 5 show that the RMSEAs for the CFA analyses were 0.04, indicating a close fit, while the
GFI (0.88) is reasonably high in the range of zero (0) to one (1).

Figure ‎5 2 : Results of CFA

5.8 CAUSATION OR CAUSALITY
As causal research seeks to identify the cause-and-effect relationships between variables, in other
words, how the occurrence of one event will cause the occurrence of another event, SEM satisfies
this requirement by testing the relationship between variables which is based on a strong
theoretical justification. Use of SEM is also motivated by the fact that it makes path analysis
possible. Path analysis to model development ensures that the independent variables are well fitted
into the model. In the context of the present study, the proposed variables will be subjected to
path analysis.
5.8.1 The path models investigated in the present study
Structural equation models are models that permit an investigation into the causal relationship
among latent variables or constructs. In the present study, the causal module was constructed to
measure and investigated the relationships between Information Technology, Strategic management,
Shared Values, leadership and Employees, Business Process and organizational effective’s variables.

Figure ‎5 3: Cause-and-Effect relationships
Figure ‎5 4: Cause-and-Effect relationships
5.8.2 Cause-and-Effect relationships between Strategic Management (SM) and Organizational
Effectiveness (OE)

The path model depicted in Figure ‎5 4, including the correlations illustrated in
Table ‎5 7, was analyzed by means of the AMOS statistical software package and the results recorded
in Table ‎5 6 and Table ‎5 7.

Estimate
ESM <— SM 0.021
ESB <— SM 0.118
BP <— SM 0.302
OS <— SM 0.083
Table ‎5 6 : Standardized Regression Weights- SM

Estimate
SM <–> ITA 0.381
SM <–> ITB 0.347
SM <–> ITS 0.451
SM <–> LS 0.717
SV <–> SM 0.56
Table ‎5 7: Correlations with SM
Table ‎5 6 shows a significant positive relationship (0.08) between SM and OS. This means that the
more these SM the stronger their OS intent will be.
Table ‎5 6 also indicates a significant positive relationship (0.30) between SM and the BP. Also a
significant positive relationship (0.12) between SM and the ESB.
Table ‎5 7 shows that in this path model all independent variables were significantly correlated
with SM.
The empirical results reveal that SM do significantly influence on OE and BP. Based on the
empirical results (path coefficients) summarized in Table ‎5 6.This means that the revised
hypothesis (H4.1) “To what extent the strategic management has a positive affect the organizational
effectiveness “is supported, as well as the hypothesis (H4.2) “Strategic management improves the
business processes in accordance with the company’s strategy” is supported, the hypothesis (H4.3)
“Strategic management influence on the Employees’ behavior” is supported,

5.8.3 Cause-and-Effect relationships between Leadership (LS) and (SM) and Organizational
Effectiveness (OE)

Table ‎5 8 shows a significant positive relationship (0.08) between LS and OS. This means that the
more these LS the stronger their OS intent will be.

Standardized Regression Weights Estimate
ESM <— LS 0.452
BP <— LS 0.272
OS <— LS 0.08
Table ‎5 8: Standardized Regression Weights- LS
Correlations: Estimate
ITS <–> LS 0.480
ITB <–> LS 0.493
ITA <–> LS 0.406
SM <–> LS 0.717
SV <–> LS 0.516
Table ‎5 9
Table ‎5 8 also indicates a significant positive relationship (0.45) between LS and the ESM. However
there are a significant positive relationship (0.27) between LS and the BP.
Table ‎5 9 shows that in this path model all independent variables were significantly correlated
with LS.
The empirical results reveal that LS do significantly influence on OE and BP. Based on the
empirical results (path coefficients) summarized in Table ‎5 8.This means that the revised
hypothesis (H2.1) “The leadership style has a positive impact on organizational effectiveness “is
supported, as well as the hypothesis (H2.2) “The leadership style has an impact on the Employees’
motivation.” is supported. In addition the hypothesis (H3.3) “The leadership style has an impact on
the business processes” is supported

5.8.4 Cause-and-Effect relationships between Shared Values (SV) and Organizational Effectiveness
(OE)
Table ‎5 10 shows a not significant positive relationship (0.002) between SV and OS, also indicates
a significant negative relationship (-0.28) between SV and the ESB. However there is no significant
relationship (0.015) between SV and the BP.
Standardized Regression Weights Estimate
BP <— SV 0.015
ESB <— SV -0.247
OS <— SV 0.002
Table ‎5 10
Correlations: Estimate
SV <–> SM 0.560
SV <–> ITA 0.431
SV <–> ITS 0.578
SV <–> ITB 0.168
SV <–> LS 0.516
Table ‎5 11
Table ‎5 11 shows that in this path model all independent variables were significantly correlated
with SV.
The empirical results reveal that SV do significantly influence on ESB However there are not a
significantly effect on and BP & OE. Based on the empirical results (path coefficients) summarized
in Table ‎5 10.This means that the revised hypothesis (3.1) “The organization develops and motivates
shared value has a positive impact on organizational effectiveness “Not supported, as well as the
hypothesis (3.3) “To what extent the Shared Value has a positive impact to improve the Business
Process” is not supported. However, the hypothesis (3.2) “To what extent the Shared Value have an
positive impact on the on the Employees’ behavior” is support
5.8.5 Cause-and-Effect relationships between Information Technology (IT) and Organizational
Effectiveness (OE)
IT Behavior

The empirical results summarized in Table ‎5 12 shows that believes the use of information
technology have a significant negative impact on the Employees’ behavior (-25%) and motivation
(26%), However, The results shows that ITB does not have a significant impact on the organizational
performance.

Standardized Regression Weights Estimate
ESB <— ITB -0.249
ESM <— ITB 0.256
OE <— ITB -0.010
Table ‎5 12
Correlations: Estimate
ITB <–> ITS 0.402
ITB <–> LS 0.493
ITA <–> ITB 0.562
SM <–> ITB 0.347
SV <–> ITB 0.168
Table ‎5 13
Table ‎5 14 shows that believes of use the IT is correlated with SM and SV
As conclusion:
Finally, the empirical results do not support the hypothesis H.b1 that the Organization believes
that the use of information technology has positive On Organizational Performance”. However, the
empirical results do support the hypothesis H.b2 that: “The Organization believes that the use of
information technology has an impact on Employees’ behavior in accordance with the company’s
strategy”.
The hypothesis H.b3 that: “The Organization believes that the use of information technology has an
impact on Employees’ Motivation in accordance with the company’s strategy” is supported.

IT Satisfaction

IT satisfaction has significant relationship (0.39) between ESB, also indicates not a significant
relationship (0.02) between ESM and (0.03) the OE.
Standardized Regression Weights Estimate
ESM <— ITS 0.018
ESB <— ITS 0.390
OS <— ITS 0.026
Table ‎5 15
Correlations: Estimate
ITB <–> ITS 0.402
ITA <–> ITS 0.624
SV <–> ITS 0.578
SM <–> ITS 0.451
ITS <–> LS 0.480
Table ‎5 16

This result not supports the hypothesis H.s1 “To what extent the IT satisfaction has positive
impact on Employees’ behavior in accordance with the company’s strategy” and H.s3 ““IT’
satisfaction has positive On Organizational effectiveness” is not supported, However the result
support H.s2 “To what extent the IT satisfaction has positive impact on Employees’ motivation in
accordance with the company’s strategy” is supported.

IT Implementation

IT implementation has significant relationship (0.14) between BP and (0.16) ESM, also indicates a
significant relationship (0.13) between ITA and the OE.
Standardized Regression Weights Estimate
BP <— ITA 0.143
ESM <— ITA 0.163
ESB <— ITA -0.017
OS <— ITA 0.129
Table ‎5 17
Correlations: Estimate
ITA <–> ITB 0.562
ITA <–> ITS 0.624
ITA <–> LS 0.406
SM <–> ITA 0.381
SV <–> ITA 0.431
Table ‎5 18
This empirical result supports the hypothesis H.a1 “The Organization applies the information
technology has positive impact Employees’ motivation in accordance with the company’s strategy” and
H.a2 “The Organization applies the information technology to improve the business processes in
accordance with the company’s strategy” is Support, and H.a3: “The Organization applies the
information technology to improve the on organizational effectiveness” is support

 

5.8.6 Cause-and-Effect relationships between Employees (ES) and Organizational Effectiveness (OE)

The empirical results reveal that the Employees’ behavior and motivation orientation does leads to
increased Organizational Effectiveness. This result supports the hypothesis H5.1 “Employees’
behavior is positively related with organizational effectiveness” and H5. 2 “Employees’ motivation
has a positive impact on organizational effectiveness”

Standardized Regression Weights Estimate
OS <— ESB 0.089
OS <— ESM 0.278
Table ‎5 19 : Standardized Regression Weights- ES

5.8.7 Cause-and-Effect relationships between Business Processes (BP) and Organizational
Effectiveness (OE)
As shown in Table ‎5 19 that the existing and using Business processes has a significant
relationship and lead to enhance the effectiveness of the organization by 29.3%.

Standardized Regression Weights Estimate
OS <— BP 0.293
Table ‎5 20 : Standardized Regression Weights- BP
Finally, the empirical results do support the hypothesis H6.1 that” “There exist association among
the Processes of firms and organizational effectiveness”

5.8.8 Direct and In-Direct influence on Organizational Effectiveness

The aim of this study is to explore the direct and indirect factors affecting on organizational
Effectiveness. Indirect factors being those that first influence Business Processes and Employees’
behavior and motivation, and then affecting organizational Effectiveness as shown in Figure ‎5 5&
Table ‎5 21.
Direct Influence Group on Organizational Effectiveness:
As shown in Figure ‎5 5 there are many factors are influencing direct the Organization
effectiveness.

In-Direct Influence Group on Organizational Effectiveness

As shown in Figure ‎5 6 there significant indirect impact on BP, ESB and ESM
Figure ‎5 6: Direct and In-Direct Influence on OE
Direct Effect In-Direct Effect
OE <— BP 0.293 BP <— SM 0.295
BP <— LS 0.271
BP <— ITA 0.139
BP <— SV 0.015
OE <— ESB 0.089 ESB <— ITS 0.390
ESB <— SM 0.118
ESB <— ITA -0.017
ESB <— SV -0.247
ESB <— ITB -0.249
OE <— ESM 0.279 ESM <— LS 0.446
ESM <— ITB 0.268
ESM <— ITA 0.156
ESM <— SM 0.013
ESM <— ITS 0.007
OE <— ITA 0.129
OE <— SM 0.084
OE <— LS 0.080
OE <— ITS 0.027
OE <— SV 0.002
OE <— ITB -0.012
Table ‎5 21: Direct and In-Direct Influence on OE

5.9 Qualitative Data Analysis
The objective of in-depth interviews is to unearth preliminary issues to help the researcher to
focus on issues which require in-depth investigation and to transfer the framework to an a priori
theoretical model for empirical testing. In-depth interviews can provide information which
observation does not. Open-ended interviews were conducted with a number of executive management to
recreate every variable concerned and understand the causal relationships and linkages inherent in
the process of factors identification. These people are important sources of valuable firsthand
information. At the beginning, the researcher started interviewing some junior executive level
staff and gradually moved up to higher position levels. The main reason for this was that the
researcher may not have been able to return to interview the executive level again once the
researcher has missed some points or needs further answers. Therefore, by starting with the lower
position level staff and moving up, the researcher can gain more insight into what the researcher
wants to know and what the researcher should ask the executives. The researcher sometimes used
telephone interviews or internet in case of verification and confirmation. All interviews were
conducted in Arabic and English and each interview took around one and a half hours.
5.9.1 Strategic Stance and Organizational Effectiveness
The findings indicated that typically the firm employs different strategic stance based on the
situation and leader’s vision. An analyzer strategic as shown in the cases of Zain and Viva. Whilst
Ooredoo viewed that their strategic approach the Prospector type which is the main reason of them
being a market leader in focusing on new product development.
Typically for the analyzer type, the firms try to capitalize on the best of both prospector and
defender types. They seek to minimize risk and maximize opportunity for profit, moving into new
products or new markets only after viability has been established by prospectors, and then
imitating from these prospectors. They also seek a hybrid of both flexibility and stability during
environmental changes. Parts of these organizations have high levels of standardization, and
automation for efficiency. Other parts are adaptive, to enhance flexibility. In this way, they seek
structures that can accommodate both stable and dynamic areas of operation. If situations change
rapidly, then the demand of organizations to move fully in either direction or their ability to
take such action is severely limited

Zain – as over all the organization’s strategy focuses on improving the efficiency of their
operations, and maintain the customer satisfaction. Therefore, Zain a cross history, It went
through strategies as following:
From 2003-2010 :Prospector – so move from 600,000 Subscribers to 73 million subscribers, which is
the main reason of them being a market leader in focusing on new product development and
penetration new area.
From 2010 – now: varied among ‘Reactor’, ‘Defender’, and ‘Analyzer’.

Ooredoo: varied among ‘Defender’, and ‘Analyzer’
“We assessed our organization as Defender and are now changing to be more of an analyser type
because we have been quite strongly analysing the situation and all the risks that may affect the
business, so we are moving prospector as needed.”

VIVA: Viva launched Dec 2008, having a clear vision to lead Kuwait market, so within 7 years it
became the 2nd market share 33% against 42% for Zain (more 30 years ) and 30% Ooredoo ( more than
15 years); we assessed our organization as prospector and main strategy, therefore we consider
Analyzer strategy for the longtime strategy.

5.9.2 Strategic leadership and Organizational Effectiveness

The key task of strategic leadership is to give the organization a sense of direction; strong
leaders must have ability to define the organization’s vision/mission, maintain flexibility,
formulate and implement strategies, create trust, and empower and align people to initiate changes
it becomes part of the culture of the organization
Vision is the first component of strategic leadership, without vision/mission, strategic leaders
cannot lead follower and cannot adjust the organization to changing environments, Vision /mission
focuses on the ability to create and anticipate the future.
Process includes the ability to communicate vision, align allocation of internal resources to cope
with external opportunities. Integrity is aimed at empowering people and creating trust and loyalty
to the organization
– There are a big gap between Shareholders (owners) and the executive management
– Owners’’ intervention in running operation (Recruitment, Employees’ promotions … etc.)

5.9.3 Information Technology and Organizational Effectiveness

In common: the organization has continually improved its information technology and data system,
with sufficient data for decision making. The Board of Directors received sufficient information
ahead of meetings, of which the minutes of each meeting summarizing directorial opinions are kept.
The evidence that the current information technology system facilitates their operations, and makes
them more flexible, the staff showed that they have more flexibility in decision-making, but still
work under the standard operating procedures.
Effective work processes and highly competent human resources are essential for business
development to be more efficient, transparent, and competitive, so the company is focusing on
extending its employees’ competency while improving their satisfaction and engagement toward the
organization, as well as introducing effective management tools and information technology that can
be adapted to the company in order to enhance business competitiveness.

5.9.4 Employees’ behavior and Organizational Effectiveness
Employees are the main asset in the company, they are business partners, we empowering people and
creating trust and loyalty to the organization this is due to our believe that Employees’ behavior
have a high impact on the organization performance.
– There are a difficulty to get the proper resource with proper qualification in our region.
5.10 SUMMARY
In this chapter the empirical results of the present study were reported. The impact on
organizational effectiveness among the various leadership and organizational variables was also
discussed. In the next chapter these findings will be interpreted with particular reference to
their implications for management.
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