scholarly journals A harmonized method for automatable life cycle sustainability performance assessment and comparison of civil engineering works design concepts

2020 ◽  
Vol 588 ◽  
pp. 052023
Author(s):  
K Ek ◽  
A Mathern ◽  
R Rempling ◽  
M Karlsson ◽  
P Brinkhoff ◽  
...  
Keyword(s):  
Life Cycle ◽  
Performance Assessment ◽  
Civil Engineering ◽  
Sustainability Performance ◽  
Design Concepts

scholarly journals Life Cycle Sustainability Performance Assessment Method for Comparison of Civil Engineering Works Design Concepts: Case Study of a Bridge

2020 ◽  
Vol 17 (21) ◽  
pp. 7909 ◽  
Author(s):  
Kristine Ek ◽  
Alexandre Mathern ◽  
Rasmus Rempling ◽  
Petra Brinkhoff ◽  
Mats Karlsson ◽  
...  
Keyword(s):  
Life Cycle ◽  
Performance Assessment ◽  
Civil Engineering ◽  
Sustainability Assessment ◽  
Concrete Slab ◽  
Assessment Method ◽  
Sustainability Performance ◽  
Design Concepts ◽  
Composite Bridge

Standardized and transparent life cycle sustainability performance assessment methods are essential for improving the sustainability of civil engineering works. The purpose of this paper is to demonstrate the potential of using a life cycle sustainability assessment method in a road bridge case study. The method is in line with requirements of relevant standards, uses life cycle assessment, life cycle costs and incomes, and environmental externalities, and applies normalization and weighting of indicators. The case study involves a short-span bridge in a design-build infrastructure project, which was selected for its generality. Two bridge design concepts are assessed and compared: a concrete slab frame bridge and a soil-steel composite bridge. Data available in the contractor’s tender phase are used. The two primary aims of this study are (1) to analyse the practical application potential of the method in carrying out transparent sustainability assessments of design concepts in the early planning and design stages, and (2) to examine the results obtained in the case study to identify indicators in different life cycle stages and elements of the civil engineering works project with the largest impacts on sustainability. The results show that the method facilitates comparisons of the life cycle sustainability performance of design concepts at the indicator and construction element levels, enabling better-informed and more impartial design decisions to be made.

scholarly journals Sustainability Performance Assessment Using Self-Organizing Maps (SOM) and Classification and Ensembles of Regression Trees (CART)

2021 ◽  
Vol 13 (7) ◽  
pp. 3870
Author(s):  
Mehrbakhsh Nilashi ◽  
Shahla Asadi ◽  
Rabab Ali Abumalloh ◽  
Sarminah Samad ◽  
Fahad Ghabban ◽  
...  
Keyword(s):  
Performance Assessment ◽  
Prediction Accuracy ◽  
Prediction Models ◽  
Sustainability Assessment ◽  
Regression Trees ◽  
Machine Learning Techniques ◽  
Coefficient Of Determination ◽  
Sustainability Performance ◽  
Learning Techniques ◽  
Self Organizing

This study aims to develop a new approach based on machine learning techniques to assess sustainability performance. Two main dimensions of sustainability, ecological sustainability, and human sustainability, were considered in this study. A set of sustainability indicators was used, and the research method in this study was developed using cluster analysis and prediction learning techniques. A Self-Organizing Map (SOM) was applied for data clustering, while Classification and Regression Trees (CART) were applied to assess sustainability performance. The proposed method was evaluated through Sustainability Assessment by Fuzzy Evaluation (SAFE) dataset, which comprises various indicators of sustainability performance in 128 countries. Eight clusters from the data were found through the SOM clustering technique. A prediction model was found in each cluster through the CART technique. In addition, an ensemble of CART was constructed in each cluster of SOM to increase the prediction accuracy of CART. All prediction models were assessed through the adjusted coefficient of determination approach. The results demonstrated that the prediction accuracy values were high in all CART models. The results indicated that the method developed by ensembles of CART and clustering provide higher prediction accuracy than individual CART models. The main advantage of integrating the proposed method is its ability to automate decision rules from big data for prediction models. The method proposed in this study could be implemented as an effective tool for sustainability performance assessment.

scholarly journals A study of the impact of information disclosure quality on the efficiency of corporate investment—Based on civil engineering listed companies

2020 ◽  
Vol 198 ◽  
pp. 03032
Author(s):  
Liying Zhang
Keyword(s):  
Life Cycle ◽  
Civil Engineering ◽  
Listed Companies ◽  
Investment Efficiency ◽  
Disclosure Quality ◽  
High Quality ◽  
Life Cycle Stages ◽  
Quality Disclosure ◽  
The Impact

Most of the existing studies on the impact of disclosure quality of listed companies on the investment efficiency of enterprises are based on the static level, and the article investigates the evolution of disclosure quality on the investment efficiency of enterprises from the dynamic level by dividing the life cycle of enterprises. Taking the data of Shenzhen civil engineering companies from 2013-2017 as the research sample, it uses multiple regression analysis to empirically test the impact of disclosure quality of listed companies on the investment efficiency of enterprises at different life cycle stages. The results show that when no distinction is made between life cycle stages, high quality disclosure can significantly inhibit the inefficient investment behavior of firms; in the growth and maturity samples, high quality disclosure can significantly inhibit underinvestment and overinvestment; in the recessionary samples, high quality disclosure can significantly inhibit underinvestment and has no significant effect on overinvestment.

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