The complex dynamics inherent to the context of decision-making in the construction
industry requires more rigorous application of analytics. However, effective frameworks to …

This research proposes a systematic data-driven analytics protocol and case studies that
can help decision makers in the construction industry embrace the practice of using data to …

Abstract The Purdue Index for Construction (Pi-C) was developed to gauge the health of the
construction industry. It is a composite index consisting of five dimensions: economic …

Technological advancements focusing on effective and efficient information modeling,
visualization, resource tracking, and collaboration have gained substantial traction in the …

The Architectural/Engineering/Construction (AEC) industry comprises a large portion of the
global economy, contributing significantly to gross domestic product (GDP) and employment …

The Purdue index for construction (Pi-C) was previously developed to facilitate and promote
data-driven decision-making. Pi-C is an analytical platform that allows stakeholders and …

In recent years, the digital world has experienced an explosion in the magnitude of data
being captured and recorded in various industry fields. Accordingly, big data management …

Purpose This paper aims to review the latest management developments across the globe
and pinpoint practical implications from cutting-edge research and case studies …

Given the highly visible nature, transportation infrastructure construction projects are often
exposed to numerous unexpected events, compared to other types of construction projects …

The increasing adoption of digital technology and the rapid proliferation of data have
spurred the application of data analytics and big data to drive smart project and asset …