PRACTICE OF CONSTRUCTION SCHEDULING AND ITS IMPACT ON DELAY CLAIM ANALYSIS

Abstract

Construction schedules should sufficiently and accurately provide the necessary information to measure effect of a delay event on: succeeding activities, project duration and project cost. However, it was concluded that programs being submitted by contractors in the Ethiopian context don't assist to analyze delays. Performance of delay claims analysis in Ethiopian context is usually very low in terms of accuracy because analysis is little based on reliable and sufficient schedule information. The objective of this thesis was to evaluate practice and challenges of construction scheduling in view of delay analysis in Ethiopia, the impact on delay claim analysis and propose a scheduling framework to improve performance of DCA. In collecting data, survey questionnaire was delivered to purposively selected construction professionals and 155 complete responses were collected. The data was checked for construct validity, content validity and reliability. Mean scores of factors were calculated and one sample T-tests were performed to evaluate relative significance. Multiple regression analysis was conducted to predict impact of the scheduling practice factors and documentation of as￾built records on performance of delay claim analysis. Results of the study showed that the construction scheduling practice in Ethiopia is below satisfactory in providing accurate and sufficient information for delay analysis in all dimensions studied. Low Responsiveness of Contractors’ Top management to Schedules (1), Lack of Technical knowledge and skill of Scheduling (2), Absence of National Scheduling Standards (3) and Task of iteration in a resource constrained environment (4) were identified challenge factors of construction scheduling in Ethiopia. Task of iteration in a resource constrained environment was found the most challenging factor. Reliability of Schedule (1), Accuracy and Timely Communication of Update Schedules (2), Documentation of Old Schedules and the Schedule 1 2 basis (3) and Conciseness of Schedule (4) were identified as scheduling practice factors impacting delay claim analysis. Results of regression analysis showed that Documentation of as built records has the most prediction of the impact on delay analysis performance whereas Conciseness of Schedule has the least prediction. The regression model was significant with F (5,149) = 20.145, P < 0.001. A case study that confirmed results of the quantitative analysis was also conducted. Finally, a scheduling framework to improve performance of delay claim analysis was developed. The developed framework indicates roles of stakeholders in mitigating the impacting factors. The findings of this study are helpful to improve performance of DCA and the scheduling practice because it revealed the status of the practice, identified challenges to be tackled and provided a framework guide for improvement.