Bunuen, Jan Renelle S., author.
Effects of temperature on labor productivity : a mathematical model for construction workers in Tuguegarao City [manuscript] / Jan Renelle S. Bunuen, Leighy H. Galamay, Jean Narcisa C. Taberna. - ©2025 - xii, 69 pages ; 29 cm.
Thesis (B.S.) -- Cagayan State University, 2025.
The southwest monsoon, locally known as Habagat, is a weather phenomenon that brings intense rainfall and strong winds to the Philippines, particularly affecting western regions from May to October. These extreme weather conditions pose significant challenges to the construction industry, which is highly sensitive to environmental disruptions. In typhoon-prone areas like Cagayan, such weather patterns have led to repeated instances of cost and time overruns in infrastructure projects, particularly road construction. Despite the evident impact of Habagat, limited research has explored how extreme weather events influence construction overruns using advanced statistical methods. This study investigates the extremity of cost and time overruns in road construction projects during Habagat season in the Third District of Cagayan. Generalized Extreme Value (GEV) models, both stationary and non-stationary, were employed using monthly time series data. Rainfall and windspeed, analyzed for trends, were used as covariates to model non-stationarity in the GEV parameters. Results revealed an increasing trend in rainfall and an abrupt change in windspeed over time, indicating non- stationary behavior in the time series data. Using the extRemes package in R, several GEV models were developed and compared. For cost overruns, the best-fitting non-stationary model included an exponential scale function with rainfall as a covariate, suggesting that higher rainfall significantly increases the spread of extreme cost overrun values. For time overruns, the optimal model featured a linear location and exponential scale function with windspeed as its covariate, highlighting that increased wind intensifies the frequency and magnitude of extreme project delays. Furthermore, the non-stationary models demonstrated better overall fit based on parameter estimates. Return level analysis indicated that non-stationary assumptions tend to overestimate future extremes. Therefore, this study underscores the importance of incorporating non-stationary models and relevant climatic covariates to enhance the understanding and management of construction risks during extreme weather conditions like Habagat.
Keywords: Habagat, Construction Overruns, Extreme Value Analysis, Generalized Extreme Value, Stationary, Non-Stationary
Civil 0122 / 2025 c.1
Effects of temperature on labor productivity : a mathematical model for construction workers in Tuguegarao City [manuscript] / Jan Renelle S. Bunuen, Leighy H. Galamay, Jean Narcisa C. Taberna. - ©2025 - xii, 69 pages ; 29 cm.
Thesis (B.S.) -- Cagayan State University, 2025.
The southwest monsoon, locally known as Habagat, is a weather phenomenon that brings intense rainfall and strong winds to the Philippines, particularly affecting western regions from May to October. These extreme weather conditions pose significant challenges to the construction industry, which is highly sensitive to environmental disruptions. In typhoon-prone areas like Cagayan, such weather patterns have led to repeated instances of cost and time overruns in infrastructure projects, particularly road construction. Despite the evident impact of Habagat, limited research has explored how extreme weather events influence construction overruns using advanced statistical methods. This study investigates the extremity of cost and time overruns in road construction projects during Habagat season in the Third District of Cagayan. Generalized Extreme Value (GEV) models, both stationary and non-stationary, were employed using monthly time series data. Rainfall and windspeed, analyzed for trends, were used as covariates to model non-stationarity in the GEV parameters. Results revealed an increasing trend in rainfall and an abrupt change in windspeed over time, indicating non- stationary behavior in the time series data. Using the extRemes package in R, several GEV models were developed and compared. For cost overruns, the best-fitting non-stationary model included an exponential scale function with rainfall as a covariate, suggesting that higher rainfall significantly increases the spread of extreme cost overrun values. For time overruns, the optimal model featured a linear location and exponential scale function with windspeed as its covariate, highlighting that increased wind intensifies the frequency and magnitude of extreme project delays. Furthermore, the non-stationary models demonstrated better overall fit based on parameter estimates. Return level analysis indicated that non-stationary assumptions tend to overestimate future extremes. Therefore, this study underscores the importance of incorporating non-stationary models and relevant climatic covariates to enhance the understanding and management of construction risks during extreme weather conditions like Habagat.
Keywords: Habagat, Construction Overruns, Extreme Value Analysis, Generalized Extreme Value, Stationary, Non-Stationary
Civil 0122 / 2025 c.1