Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.8
3.9
Journals
Sustainability
Special Issues
Advances in Construction Performance Prediction Techniques: Perspectives for Sustainability
sustainability-logo
Submit to Sustainability Review for Sustainability Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Advances in Construction Performance Prediction Techniques: Perspectives for Sustainability

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Engineering and Science".

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 4493

Special Issue Editors

Prof. Dr. Sangwon Han

E-Mail Website
Guest Editor
Department of Architectural Engineering, University of Seoul, Seoul 02504, Korea
Interests: construction simulation; construction economics; construction finance and accounting; feasibility studies; asset management
Special Issues, Collections and Topics in MDPI journals
Dr. Woon Seong Jeong

E-Mail Website
Guest Editor
Department of Architectural Engineering, Chungbuk National University, Cheongju 28644, Republic of Korea
Interests: sustainable design and construction management system using building information model and energy simulation model; intelligent and sustainable project management using emerging information and communication technology; decision support system to support the collaborative design process; data modeling to support reliable project planning and control; object-oriented physical modeling for integrated building performance simulation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Successful completion of a sustainable construction project necessitates periodical monitoring of actual performance and taking corrective actions if necessary. For this, feasible and optimal performance should first be planned so that it can be compared to actual performance. Until now, the construction industry has striven to develop various tools and methodologies that can systematically predict planned performance, such as time, money, quality, information, labor, equipment, materials, and so forth.

This Special Issue is to solicit original theoretical, methodological, and empirical research papers associated with advances in construction performance prediction techniques. Topics of interest include, but are not limited to, the following:

  • Simulation
  • Statistical techniques
  • Genetic algorithms
  • Artificial neural network
  • Expert system
  • Case-based reasoning
  • Artificial intelligence
  • Virtual reality/augmented reality
  • Smart construction
  • Big data

Prof. Dr. Sangwon Han
Prof. Dr. Woon Seong Jeong
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. Sustainability is an international peer-reviewed open access semimonthly 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 2400 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 performance
  • construction planning
  • construction performance prediction
  • construction performance optimization
  • construction performance monitoring
  • prediction techniques

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

23 pages, 3767 KiB  
Article
Comparison of the Technical Efficiency of Construction Industries—A Case Study of Taiwan and Mainland China
by Wei Tong Chen, Adiqa Kausar Kiani, Ming-Tsung Wu, Hew Cameron Merrett and Chih-Hsing Wang
Sustainability 2023, 15(2), 941; https://0-doi-org.brum.beds.ac.uk/10.3390/su15020941 - 04 Jan 2023
Cited by 1 | Viewed by 2133
Abstract
A strong construction industry is critical to any country’s economic and infrastructural development. Facing declining business prospects in the domestic market, Taiwanese construction firms have sought new opportunities overseas, particularly in the mainland Chinese market. Without an adequate understanding of the market, making [...] Read more.
A strong construction industry is critical to any country’s economic and infrastructural development. Facing declining business prospects in the domestic market, Taiwanese construction firms have sought new opportunities overseas, particularly in the mainland Chinese market. Without an adequate understanding of the market, making such investments involves significant risks. To better understand the differences in the markets, this study investigates the technical efficiency (TE) of the Taiwanese construction industry compared to mainland China. The focus was on TE values of construction companies across the two markets as well as the strengths and weaknesses to help inform the decision-making process. The TE evaluation was completed using the stochastic frontier approach (SFA) with a subinput efficiency model to evaluate three inputs (assets, costs, and labor) of 123 construction companies with 59 companies in mainland China and 64 companies in Taiwan. Results show that for the key asset investment factors in Taiwan’s construction industry, TE is lower than that in mainland China. However, Taiwan’s construction industry was found to have higher labor efficiency than mainland China. Relative to mainland Chinese companies, Taiwanese companies have advantages in both labor inputs and revenue outputs but are disadvantaged in terms of the firm and market size. This study shows that Taiwanese construction firms are positioned to pursue expansion into mainland China, ideally by establishing cooperative alliances. Results also show that government policy needs to ensure construction companies are supported by increased economic freedom and reduced restrictions, as these positively correlate with the revenue of local construction companies. Full article
(This article belongs to the Special Issue Advances in Construction Performance Prediction Techniques: Perspectives for Sustainability)
►▼ Show Figures

Figure 1

21 pages, 7363 KiB  
Article
Cost Deviation Model of Construction Projects in Saudi Arabia Using PLS-SEM
by Abdullah M. Alsugair
Sustainability 2022, 14(24), 16391; https://0-doi-org.brum.beds.ac.uk/10.3390/su142416391 - 07 Dec 2022
Cited by 10 | Viewed by 1765
Abstract
Miscalculations during cost estimation can have adverse effects on construction projects, including delaying or canceling planned projects, reducing project scope, and creating considerable financial risks for both owners and contractors. The objective of this research was to identify the major factors that cause [...] Read more.
Miscalculations during cost estimation can have adverse effects on construction projects, including delaying or canceling planned projects, reducing project scope, and creating considerable financial risks for both owners and contractors. The objective of this research was to identify the major factors that cause cost deviation and study the effect of the interaction between these factors on cost deviation prior to the tender phase of construction projects in the Kingdom of Saudi Arabia. This was accomplished by carrying out a comprehensive literature review of the factors affecting cost deviation; implementing a survey questionnaire for project participants, including contractors, consultants, and clients, who are aware of the construction industry in Saudi Arabia; and developing a model for cost deviation based on the questionnaire data using the partial least square structural equation model (PLS-SEM). The cost deviation model was developed, and the PLS-SEM provided the critical factors affecting cost deviation and gave theoretical support for the study’s conceptual framework. The results revealed that the problem is shared by the owners and contractors, as the factors with the highest rankings were project characteristics, contractual procedures, and estimator performance. The study also showed that the issue of cost deviation is more important to owners than contractors, as the predictive relevance of project characteristics, contractual procedures, and estimator performance were 0.229, 0.335, and 0.197, respectively, for the client–consultant model, and 0.117, 0.118, and 0.292, respectively, for the contractor model. The results indicate the need to control the highest-ranked factors to enhance the efficiency of the cost estimation process. This study contributes to the body of knowledge by generating the PLS-SEM model that takes into account the indirect relationships among affecting cost deviation factors and considers these relationships while preparing the bid to reduce the deviation cost. Full article
(This article belongs to the Special Issue Advances in Construction Performance Prediction Techniques: Perspectives for Sustainability)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop