An Examination of the Level Of 5D BIM Use and Benefits on Construction Project Delivery

for validating interpretations and conclusions. This documentation encouraged transparency and accountability during the study process. The quantitative data gathered from a semi-structured questionnaire were analysed using statistical tools and methods. This entails a thorough classification of the data to uncover reoccurring themes, categories, and patterns of meaning. The analysis began with familiarisation with the data, followed by the creation of a coding scheme based on the research goals. Open coding was used to develop initial codes, which would then be gathered and organised into suitable themes. The findings were given using descriptive statistics accompanied by statements from participants, providing a thorough overview of the data. In this study, data analysis was carried out quantitatively; quantitative data received from surveys were analysed using IBM Statistical Package for Social Sciences version 26.0 and analysis software. The primary statistical technique used was based on each target that was originally scripted at the start of the investigation. To achieve the first goal, which was to determine the extent of 5D BIM use, attributes, and benefits in building project management in Rivers state. Descriptive statistics in the form of frequency were applied. To accomplish the second goal, which was to investigate the perceived benefits of 5D BIM use in building project management in Rivers state. Factor analysis was applied. In attaining the third aim, which was IJEMT to determine the impact of perceived benefits of 5D BIM on construction project planning and execution in Rivers State. Multiple regression was employed to accomplish this. Finally, the fourth goal was to assess the obstacles that 5D BIM utilisation poses in building project management in Rivers state. The severity index was utilised to achieve that. Results The results reveal the demographic distribution of respondents, as well as responses to questions about the study's main objectives. The data was statistically analysed, and conclusions were drawn based on the results. Table 2 shows the response rate and summary of the questionnaire distribution. Table 2: Response rate from respondents S/n Professionals Population Sample Samples returned Samples used 1 Quantity surveyors 125 48 44 43 2 Builders 147 42 36 34 3 Architects 163 52 47 45 4 Engineers 211 56 42 40 5 Project managers 89 23 20 19 6 IT construction experts 57 24 18 16 7 Estate managers 94 31 28 24 Total 886 276 235 221 Source: (Field survey 2024) 4.1.1 Demographic analysis and presentation The data collected from the questionnaire replies were analysed and presented in this paper using a frequency distribution in the form of tables. The presentation is organised in the order that the questions occur in the research questionnaires. The study selected practitioners from various construction projects operating in Rivers state, Nigeria, purposefully and particularly targeting the professionals mentioned in table 3. Table 3: Background information of the respondents Category Classifications Frequency Percentage Industry experience 0-5 years 13 5.9 6-11 years 25 11.3 12-17 years 43 19.5 19-24 years 27 12.2 Above 25 years 113 51.1 Total 221 100 Designation Quantity surveyors 43 19.5 Builders 34 15.4 Architects 45 20.4 Engineers 40 18.1 Project managers 19 8.6 IT construction experts 16 7.2 Estate managers 24 10.9 Total 221 100 Academic First degree/equivalent 99 44.8 Master’s degree 116 52.5 IJEMT qualification Doctorate degree 6 2.7 Total 221 100 Organization Government body 61 27.6 Contractor 120 54.3 Customer/user 12 5.4 Client (private) 11 5.0