II. FIELD SURVEY AND QUESTIONNAIRE PREPARATION
The objective of the questionnaire was to collect sufficient statistical and qualitative data to help in answering the questions raised by sub-problems and to help make conclusions on whether the experts hypotheses are assured or not.
The questionnaire was divided into three main sectors; A) entailed general questions of opinion mostly covering qualitative analysis, whereas sector B) and sector C) dealt with more specific questions susceptible to statistical analysis.
Sectors B) and C) were analyzed using statistical methods such as the mean, standard deviation and upper quartile. The general survey was structured in such a manner that respondents gave their opinions on the questions by hand and suggested suitable alternatives wherever applicable.
An interview was arranged with a respondent whenever there were issues in the questionnaire that needed clarification or whenever the information on specific questions disagreed with the consideration survey in an essential manner
The executed field visits and personal meetings that have been conducted enriched the initial questions list by different opinions, suggestions and proposals that considered being part of the questionnaire. The stated efforts led to the following conclusions:
1- The consultative team (designers and supervisors) does not dedicate itself in the continuous mentoring for the work and workers.
2- There is no gained benefit from the experiences extracted from the previous projects in order to avoid mistakes during the execution of current projects.
3- There is no utilization of the experience of executors that been gained from previous projects.
4- Most of projects are suffering from the inefficient of financing for projects.
5- There is no dependency on experts and responsible managers who have enough qualifications that are essential for time saving through avoiding the routine managerial procedures.
6- The consultative team has no enough time to study the project specifications carefully that may reduce change orders.
7- It is common that designers and executors have no contribution in the preparing stage of design documents.
8- The finished design documents are quickly delivered to contractors who do not have the sufficient qualifications.
9- Most of projects are suffering lack of communications between parties.
10- Most of projects are suffering lack of design software packages that enable parties to supervise and control the project.
III. SAMPLE COMPOSITION
The respondents were consisted all construction industry practitioners, including project managers (as owner), main and sub-contractors as well as consultants and engineers, the figure below shown that.
Figure I. Sample Composition According to their Party
The respondents were classified in figure II according to their educational background, there were individuals who earned the doctorate degree and were qualified with a percentage of 34%, Master's degree participant’s percentage is 8% and the remaining individuals are B.Sc. certified with percentage of 58%.
Figure II. Sample Composition According to their educational background
IV. DATA ANALYSIS
In order to assess the effect of each factor, the answers were collected from all surveyed samples (employers, engineers, contractors) whereas the questionnaire form number that been successfully received was seventy (70). According to the theory of the central margin, The results should follow the shape of normal distribution curve since Al-Rawi (1986) stated that “when we select a sample with number N from a statistical society where its center distribution µ and deviation б2, the distribution of the samples mean X almost subjected to normal distribution its mean is µ and its deviation (α/n) with the condition that sample size should be relatively big (n ≥ 30)”.
The results have been analyzed and discussed depending on the “mean” of these results which is one of central tendency (tendency of value to center on the optimal value) in addition to standard deviation value. The statistical analysis process of the results is presented in the following sub-sections.
V. EFFECT LEVEL
The effect level was assumed for each category of answer as explained in table I. This category of answer was assumed in order to facilitate the process of analyzing data results.
Table I. Evaluation of Answer Category
Effect Level Category of Answer
(Risks Factor’s Effect)
1 Has no Effect
2 Little Effect
3 Medium Effect
4 Large Effect
VI. THE ARITHMETIC MEAN
The arithmetic mean for answers calculated as follow
(Mean) = (total of number of iterations in the effect multiplied in the number of effect divided by the size of the sample).
The arithmetic mean is used in the analysis for each factor of the sectors and it is calculated as per Equation I.
n n
M = ∑Xi *Fi / ∑ Fi ……………………………………… ( Eq. I)
i=1 i=1
Whereas:
M = Arithmetic mean of the answer (rate of effects) for the questionnaire factor.
Xi = the level of category effect (i) for the questionnaire factor.
Fi = repetition of the answer category (i) for the questionnaire factor.
n= number of answers.
VII. UPPER QUARTILE
The analysis and evaluation of the questionnaire results were adopted for each factor in the questionnaire through calculating the upper quartile for the answers’ average, which represent the upper value of 75% from the values of Table I, then UQ = 3 which is the target value (Al-Rawi 1986). By this way the evaluation of the questionnaire result has been done according to the level from the target value as the following:
1- If (M > 3) then the discussion was required for the factor.
2- If (M ≤ 3) then the discussion was desired for the factor.
VIII. STANDARD DEVIATION (S)
In statistic and probability theory standard deviation (represented by the symbol σ or S) shows how much variation or “dispersion” exists from the average (mean, or expected value). A low standard deviation indicates that the data points tend to be very close to the mean, whereas high standard deviation indicates that the data points are spread out over a large range of values. Equation II presents the mathematical method that to be used in calculating the standard deviation of the collected data.
S= ………………….. (Eq. II.)
Where:
S= Standard deviation of the collected data.
Xi = the level of category effect (i) for the questionnaire factor.
X = the mean of the answer (rate of effects) for the questionnaire factor.
n= number of answers.