Data analysis of research is an important stage. The aim of data analysis is to use the evidence collected in depth to produce substantial logical conclusions and eliminating any alternative interpretations (Yin, 2009). However, there are two parts of analysis of data: analysis of quantitative data and the qualitative data. Saunders et al. (2012) argue that there is no typical process to analyse data in qualitative research. However, Collis and Hussy (2014) stated that qualitative data could be categorized into quantifying methods, such as content analysis, and the non-quantifying methods, such as general analytical procedure.
A quantitative statistical analysis has been adopted in this research on data relevance to the handover. A number of statistical approaches are used, starting with Cronbach’s Alpha test for reliability of data collected from questionnaire. Cronbach’s Alphais used to check the reliability of the items in the questionnaire. The Cronbach's Alpha values for the internal consistency of the scale and the items were all above standard agreed
79 measures (0.8) for good internal consistency. Alpha was developed by Lee Cronbach in 1951 to provide a measure of the internal consistency of a test and it is expressed as a number between 0 and 1 (Tavakol and Dennick, 2011). Per cent distributions and histogram diagrams have been applied in this study to illustrate different parameters and variables of the quantities and qualitative data and information.
Measures of variation, associations, correlation analysis, and a statistical hypothesis test as analysis of variance (ANOVA test) based on SPSS software program are used in this study. While an ANOVA test can tell the researcher whether groups in the sample differ, it cannot tell the researcher which groups differ (Tobin and Begley, 2004). A series of ANOVA has been carried out to examine whether there was an association between the variables. This is relevant to the most significant challenge to effective building handover practices in the KSA public sector construction industry and nine different benefits of total quality management in the KSA construction sector project. Also, the ANOVA used examines whether there was an association between the variables on the importance of number of benefits project data at the handover stage, as well as the most affected parameters that were affected by the building handover process and factors that are relevant to the Building Information Modelling (BIM) in the KSA construction sector.
The Chi Square statistic compares the tallies or counts of categorical responses between two (or more) independent groups. In this study, a Chi square (X2) statistic is used to investigate whether distributions of categorical variables differ from one another. In this study, with respect to the results of questionnaire parts D, E and F, it is supposed that the variable A has r levels, and variable B has c levels. The Chi Square distribution is very important because many test statistics are approximately distributed as Chi Square. In this study, the test has been used to find out the significant association within an amount of general information, the specific information related to the BIM and the importance of the project handover stage to the organisation, and all other variables of academic qualification - number of years of building handover experience in the KSA public sector construction industry, size of organisation, and the company's principal business activity.
80 In this study, the test has been used to find out the significant association within a number of general information and the specific information related to the handover. Moreover, a Tukey test has been applied to determine which groups in the sample differ. The Tukey test is most commonly used in other disciplines. This test has some advantages is to keep the level of the Type I error (i.e., finding a difference when none exists) equal to the chosen alpha level (e.g., α = .05 or α = .01) (Abdi and Williams, 2003). In order to identify which of the means are significant (after a one-way ANOVA finds a significant difference in means, a Tukey test was applied in this study for the most significant challenge to effective building handover practices in the KSA public sector construction industry) to the total quality management in the KSA construction sector project, as well as the importance of a number of benefits of project data at the handover stage. It is clear to see that the “most important” was the largest group in general, as it used the parameters most affected by the building handover process. In qualitative data, the reading and re-reading of the interviews to find similarities and differences in order to create themes and to develop categories is one of the methods to analyse qualitative data. However, there are many computer programmes that can be used for the analysis of qualitative data, such as: ATLAS.ti, NUD*DIST N6, and NVivo.
Kumar and Promma (2005) mention that researchers should use one of these computer programmes if their data is suitable for such analysis. NVivo is one of the most popular programmes used for qualitative data analysis. NVivo has many advantages, which include importing and code written data, editing the text without affecting the coding, retrieving data, searching for combinations of words in the text, reviewing and being more secure in the case of data backup.
In this study, the qualitative data from the interviews has been analysed using a general analytical procedure and NVivo software, according to the following:
● Keeping the aim and objectives of this study at the front of the mind,
● Converting the oral interview to hand writing record;
● Importing written records to the sources document folders in NVivo;
● Collecting the information for each theme and each question;
● Coding the main information related to each question in the free nodes file (Figure 3.3).
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Figure 3.3: NVivo screen shot of tree nodes with Interviewee
However, the quantitative data, which was collected from questionnaires was analysed using the Statistical Package for the Social Sciences (SPSS) software version 16. SPSS is a powerful, user-friendly software package, usually used for the statistical analysis of data. This software package is principally useful for research in the area of psychology, sociology, psychiatry, and other behavioural sciences (Landau and Everitt, 2004) and is commonly used in quantitative analysis.
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3.14 Relation between Research questions and objectives and data collection