Enhancing Productivity in Peru’s Public Works Value Chain Through AI Monitoring: A Paradigm Shift

Miranda-Hospinal O.; Valle-Cruz D.; Yrivarren-Lazo J.; Yula-Inca C.; Ronceros-Ponce K. · Communications in Computer and Information Science (2023) · DOI: 10.1007/978-3-031-43940-7_12

Resumen

Public works generally have very low productivity, from the conception of the project. An example is the Billinghurst Bridge, also called the Continental Bridge, in Madre de Dios, which connects Peru with Brazil. It took more than half a century to materialize, from the conception of the project to its start-up [1]. In this regard, artificial intelligence (AI), as an emerging technology, can help reduce time and increase productivity. The adaptation of AI to different organizations is also considered feasible, and the corresponding monitoring and measurement of its performance is of interest, particularly concerning productivity in the value chain (project cycle) of public works. This research proposes to explore not only the challenges and opportunities of AI in the productivity of public works but also the perceptions and expectations of improvement through an exploratory survey based on the instrument designed by Criado et al. [2]. This survey was addressed to engineers, architects, logisticians, experts, and arbitrators who are related to public works. The paper ends with some lessons and recommendations for researchers and professionals interested in the study area.

Instituciones: Universidad Nacional de Ingeniería