The construction industry is experiencing changes in its processes and work methods, and the advancement of new technologies in recent decades has led to a new concept known as Construction 4.0, coined in 2016 in Germany. Since its definition is still diffuse, it was deemed necessary to conduct a review on the publications in this field to grasp how this concept is being understood. For that purpose, a bibliometric analysis was conducted among 260 research articles using seven keywords. The results reveal that the number of publications is growing exponentially, with the USA, the UK, and China being leaders in this field; besides, four technologies are essential to understand Construction 4.0 at present time: 3D printing, big data, virtual reality, and Internet of Things. The results of this review suggest that further reviews should be conducted every 3 years to grasp the rapid evolution of Construction 4.0.

Construction 4.0: A Literature Review

Integrating three-dimensional road design and pavement structure analysis based on BIM

Sentiment Analysis of Social Media Twitter with Case of Anti-LGBT Campaign in Indonesia using Naïve Bayes, Decision Tree, and Random Forest Algorithm

Parametric modeling and structure verification of asphalt pavement based on BIM-ABAQUS

Industrialized construction, because of its factory-based nature, has significant potential for successful adoption of emerging technologies compared to traditional construction The main objective of this review is to identify the current mainstream research directions and research gaps in applying emerging technologies in industrialized construction This review classifies and analyzes 102 relevant articles published in the construction management-related journals in the last 15 years (ie 2004-2019) according to technology types, structural systems, project phases, and application fields Results indicate there are apparent differences in the utilization level of different technology types, the research focus for different project phases, and the number of articles for different structural systems Major benefits and challenges for different application fields are also discussed This review identifies several research gaps, including less focus on specific structural systems or technologies, inadequate research on performance assessment measures, and a lack of effective training programs Significantly, this review provides a roadmap for future research, with specific short-term and long-term solutions to address the identified research gaps

A systematic review of emerging technologies in industrialized construction

A digital construction framework integrating building information modeling and reverse engineering technologies for renovation projects

Building energy savings: Analysis of research trends based on text mining

The rapid increase in the number of online resources and academic articles has created great challenges for researchers and practitioners to efficiently grasp the status quo of building energy-related research. Rather than relying on manual inspections, advanced data analytics (such as text mining) can be used to enhance the efficiency and effectiveness in literature reviews. This article proposes a text mining-based approach for the automatic identification of major research trends in the field of building energy management. In total, 5712 articles (from 1972 to 2019) are analyzed. The word2vec model is used to optimize the latent Dirichlet allocation (LDA) results, and social networks are adopted to visualize the inter-topic relationships. The results are presented using the Gephi visualization platform. Based on inter-topic relevance and topic evolutions, in-depth analysis has been conducted to reveal research trends and hot topics in the field of building energy management. The research results indicate that heating, ventilation, and air conditioning (HVAC) is one of the most essential topics. The thermal environment, indoor illumination, and residential building occupant behaviors are important factors affecting building energy consumption. In addition, building energy-saving renovations, green buildings, and intelligent buildings are research hotspots, and potential future directions. The method developed in this article serves as an effective alternative for researchers and practitioners to extract useful insights from massive text data. It provides a prototype for the automatic identification of research trends based on text mining techniques.

Zhikun Ding

Papers

A digital construction framework integrating building information modeling and reverse engineering technologies for renovation projects

Building energy savings: Analysis of research trends based on text mining

A Thematic Network-Based Methodology for the Research Trend Identification in Building Energy Management