Estimation of contract duration in Nepal is difficult due to various complex factors nexus in the sector. Currently, the contract duration (i.e. intended time of completion) is estimated with past practice, need basis, procurement plan, geographical location, and project magnitude. However, standard methodology for the duration anticipation has become imminent to address some issues in the sector like proper budget allocation, implementation of liquidity damage and bonus provisions etc. Thus, the problem must be addressed to generate a standard practice to complete any development projects in an intended period. This study intends to validate the Bromillow’s Time Cost Model addressing the trend of building construction and associated parameters which will address significantly the existing problem. In this study, KII was conducted to identify existing building construction duration estimation. From different geographical regions, 76 building projects implemented by Department of Urban Development and Building Construction (DUDBC) are considered out of which 63 projects are studied for modification of Browmillow’s Time Cost Model and more than 20% of building data of each geographical region are used for the model validation. The working days from the calendar days were calculated by the project contracted on a year before the start of monsoon was deducted with 45 days as a rainy and inclement weather day. The exclusion weather days consist of 8 days of Asar, 30 days of Shrawan, 7 days of Bhadra of monsoon period and a duration of 365 days period due to COVID. A simple log-log linear regression analysis was carried out to develop Browmillow’s equation and the projected and observed data were analyzed to validate the model’s constant of different geographical regions. The majority of respondents in KII has adopted past practice for estimation of contract duration and related the delay of completion of the project for lack of proper project planning, inflation, resource availability, environmental and social factors, budget availability and red tapism. The linear regression for time and cost of each geographical region has revealed that cost is positively related to contract duration. The relation is strongly supported by Pearson’s correlation coefficient too. The Log-Log regression analysis of the sampled data 42-60% of data variability is only accounted by the model. The degree of model fitness R2 of each region is considered under the VI acceptance level (BAO, 2019). Also, the p-value of all regions are less than 0.05 which can be concluded that the F-Statistics is statistically significant for all regions. The results reveal that historical data is the main source of reference, with some adjustments for contextual factors such as location, size, specifications, and procurement plans. However, there is no systematic or formulaic approach to estimate the contract duration, which may lead to inaccurate and unrealistic projections. There has been a positive correlation between time and cost of the project of all regions which reveals each project’s cost increases with increment in duration. There is a significant correlation between time and costs of the project in all regions with coefficient of determination ranges from 0.42 to 0.67 and p-value less than 0.05. Also, the BTC model has high degree of prediction accuracy for all the studied geographical regions. Among studied geographical region, mountain region requires lowest duration of 44 days and terai requires highest duration of 109.9 days and hill requires moderate of 86.48 days to complete 1 lakhs project. Similarly the time duration in mountain regions is changed in higher degree of 0.48, hill region with moderate degree of 0.35 and terai region with low degree of 0.28 with respect to change in cost of the project. Despite the findings, the developed equation is deprived with other factors that has significant impact on time-cost relation. Thus, further research should be conducted to improve the accuracy and robustness of the BTC model by incorporating other variables such as quality, scope, risk, and stakeholder satisfaction etc. This study provides empirical evidence to support the applicability of the BTC model for hospital building projects in Nepal and demonstrates the importance of accurate contract duration estimation to control the project cost and avoid delays.

Keywords

BTC Model, Contract Duration Estimation, Browmillow’s Equation, DUDBC,Public Building Construction Project.

Back to list