Research on Construction Innovation and Digitization

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Construction Management, and Computers & Digitization".

Deadline for manuscript submissions: 30 June 2024 | Viewed by 3961

Special Issue Editors


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Guest Editor
College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
Interests: construction innovation; building information modeling; computer-assisted construction management; life-cycle management

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Guest Editor
School of Management, Guangzhou University, Guangzhou 510006, China
Interests: technological innovation; strategic management; global innovation; digital intelligence innovation

Special Issue Information

Dear Colleagues,

Construction management faces new challenges given the popularity of digital construction, innovative project delivery methods, emerging technologies in design and construction, and computer-assisted construction management. Project management has become more complex, and it requires advanced models and technology to improve the quality and efficiency of design, construction, operation, and maintenance of buildings. Computer technologies incorporate various processes, software, and hardware that could be used in different phases of a building life cycle. It is urgent to propose solutions through research and practice, to improve the traditional project management theory, and to accommodate the complex project management.

This Special Issue aims to publish high-quality research papers on the inter-disciplinary field of ICTs and computer applications in construction management.

We look forward to receiving your papers!

Dr. Yingnan Yang
Prof. Dr. Hongming Xie
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • construction automation
  • digital construction
  • computer-assisted construction
  • management BIM (building information modelling)
  • lifecycle management
  • construction supply chains
  • smart construction
  • advances in digital technologies for the built environment

Published Papers (2 papers)

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Research

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28 pages, 13618 KiB  
Article
Augmented Data-Driven Machine Learning for Digital Twin of Stud Shear Connections
by Gi-Tae Roh, Nhung Vu, Chi-Ho Jeon and Chang-Su Shim
Buildings 2024, 14(2), 328; https://doi.org/10.3390/buildings14020328 - 24 Jan 2024
Viewed by 770
Abstract
Existing design codes for predicting the strength of stud shear connections in composite structures are limited when adapting to constant changes in materials and configurations. Machine learning (ML) models for predicting shear connection are often constrained by the number of input variables, resembling [...] Read more.
Existing design codes for predicting the strength of stud shear connections in composite structures are limited when adapting to constant changes in materials and configurations. Machine learning (ML) models for predicting shear connection are often constrained by the number of input variables, resembling conventional design equations. Moreover, these models tend to overlook considerations beyond those directly comprising the connection. In addition, the data used in ML are often biased and limited in quantity. This study proposes a model using AutoML to automate and optimize the process for predicting the ultimate strength and deformation capacity of shear connections. The proposed model leverages a comprehensive dataset derived from experimental studies and finite element analyses, offering an advanced data-driven solution to overcome the limitations of traditional empirical equations. A digital twin model for the static design of pushout specimens was defined to replace existing empirical design codes. The digital twin model incorporates predictions of the geometry model, ultimate strength, and slip as input parameters and provides criteria for evaluating the limit state through a bilinear load–slip curve. This study advances predictive methodologies in structural engineering by emphasizing the importance of ML in addressing the dynamic and multifaceted nature of shear connection behaviors. Full article
(This article belongs to the Special Issue Research on Construction Innovation and Digitization)
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Review

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20 pages, 3349 KiB  
Review
Stakeholder Relationship in Construction Projects: A Mixed Methods Review
by Yingnan Yang, Ziyi Wei and Zhicheng Zhang
Buildings 2023, 13(12), 3122; https://doi.org/10.3390/buildings13123122 - 15 Dec 2023
Cited by 1 | Viewed by 2776
Abstract
Relationship management among different stakeholder groups plays an increasingly important role in construction innovation, which could explain the growing interest in stakeholder relationship studies of construction projects (SRCP) over the last two decades. However, most of the recent literature review studies have focused [...] Read more.
Relationship management among different stakeholder groups plays an increasingly important role in construction innovation, which could explain the growing interest in stakeholder relationship studies of construction projects (SRCP) over the last two decades. However, most of the recent literature review studies have focused on stakeholder management, and there are very few studies systematically describing what types of relationships actually exist in construction projects. To fill the gap, a mixed-methods review is conducted to explore the state-of-the-art work on SRCP. 312 relevant peer-reviewed journal articles published between 2000 and 2022 were examined and analyzed using data from the Scopus and Web of Science databases. A follow-up systematic review of the identified literature was conducted with three main objectives: identifying the main research category, summarizing the main research topics, and proposing future research directions. It was found that over the past 20 years, SRCP has been extended to a greater variety of research topics, such as information technology, which needs to take into account the multi-dimensional research agendas. Overall, this study contributes to the research field in the SRCP domain by offering insightful information on the current state of SRCP and proposing potential future directions for research. Full article
(This article belongs to the Special Issue Research on Construction Innovation and Digitization)
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