Sustainable Construction Framework in the Philippines: A Crossover Application of Back Propagation Artificial Neural Network for Industry4.0

  • Irvette Lourmarie M. Ramos-Gozun, Dante L. Silva, Kevin Lawrence M. De Jesus

Abstract

Infrastructures are one of the most significant keys in the development of the country or nation. Building these infrastructures emits thousands of carbon dioxide which leads to environmental changes and the greenhouse effect. The United Nations Environment Programme establishes the Sustainable Development Goals which address the continuing development of every country or nation without compromising the nature or environment as well as the future generation. The construction industry adopted Sustainable Development Goals to address the environmental issues, as well as the social and economic issues by this Sustainable Construction, were created. The main objective of this study is to develop a model to predict the sustainable construction practice rating considering environmental, social, and economic sustainability. The sustainable construction practice rating was developed by gathering information from the construction firms in Metro Manila through a survey questionnaire in accordance with sustainable construction practices based on environmental, social, and economic sustainability. The analysis of data includes descriptive statistics and correlational matrix analysis. The internal consistency and reliability for the sustainable construction practice rating as well as the factors affecting it was tested using the Cronbach Alpha. Four different models were developed utilizing Artificial Neural Network, these are Environmental, Social, Economic, and Sustainable Construction Practice Rating. The results showed that the most correlated and influential aspects of sustainable construction practice are social sustainability and economic sustainability, respectively. The study helped to uncover the potential of full implementation of sustainable construction in the Philippines. However, its full implementation is a complex and taxing work to carry out which will take several more years to perfect it.

Published
2020-06-01
How to Cite
Irvette Lourmarie M. Ramos-Gozun, Dante L. Silva, Kevin Lawrence M. De Jesus. (2020). Sustainable Construction Framework in the Philippines: A Crossover Application of Back Propagation Artificial Neural Network for Industry4.0. International Journal of Advanced Science and Technology, 29(08), 2640 - 2649. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/23442
Section
Articles