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Article
Publication date: 2 October 2017

Fang Shutian, Zhao Tianyi and Zhang Ying

This study aims to predict the construction cost in China, the authors purposed a fused method.

375

Abstract

Purpose

This study aims to predict the construction cost in China, the authors purposed a fused method.

Design/methodology/approach

The authors extracted 22 factors which may influence the cost and performed the correlation analysis with cost. They chose the highest 10 factors to predict cost by the fused method. The method fused the Kalman filter with least squares support vector machine and multiple linear regression.

Findings

Ten factors which affect the cost most were found. The construction cost in China can be predicted by the presented method precisely. The statistical filter method could be used in the field of construction cost prediction.

Research limitations/implications

The construction cost and construction interior factors are a business secret in China. So, the authors only collected 24 buildings’ data to perform the experiments.

Practical implications

There is no standard and precise method to predict construction cost in China, so the presented method offers a new way to judge the feasibility of projects and select design schemes of construction.

Originality/value

The authors purposed a new fused method to predict construction cost. It is the first time that the statistical filtering method was used in this field. The effectiveness was verified by the experiments. Ten factors which have a high relationship with construction cost were found.

Details

Engineering Computations, vol. 34 no. 7
Type: Research Article
ISSN: 0264-4401

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Article
Publication date: 19 June 2019

Shutian Liu, Xueshan Ding and Zeqi Tong

This paper aims to study the energy absorption properties of the thin-walled square tube with lateral piecewise variable thickness under axial crashing and the influence of the…

229

Abstract

Purpose

This paper aims to study the energy absorption properties of the thin-walled square tube with lateral piecewise variable thickness under axial crashing and the influence of the tube parameters on energy absorption.

Design/methodology/approach

In this work, the energy absorption properties of the thin-walled square tube were analyzed by theoretical, numerical and experimental approach. The numerical results are obtained based on the finite element method. The explicit formulation for predicting the mean crushing force of the tube with lateral piecewise variable thickness was derived based on Super Folding Element method. The limitation of the prediction formulation was analyzed by numerical calculation. The numerical calculation was also used to compare the energy absorption between the tube with lateral piecewise variable thickness and other tubes, and to carry out the parametric analysis.

Findings

Results indicate that the thin-walled tube with lateral piecewise variable thickness has higher energy absorption properties than the uniform thickness tubes and the tubes with lateral linear variable thickness. The thickness of the corner is the key factor for the energy absorption of the tubes. The thickness of the non-corner region is the secondary factor. Increasing the corner thickness and decreasing the non-corner thickness can make the energy absorption improved. It is also found that the prediction formulation of the mean crushing force given in this paper can quickly and accurately predict the energy absorption of the square tube.

Originality/value

The outcome of the present research provides a design idea to improve the energy absorption of thin-walled tube by designing cross-section thickness and gives an explicit formulation for predicting the mean crushing force quickly and accurately.

Details

Engineering Computations, vol. 36 no. 8
Type: Research Article
ISSN: 0264-4401

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Article
Publication date: 12 July 2022

Shutian Wang, Yan Lin, Yejin Yan and Guoqing Zhu

This study explores the direct relationship between social media user-generated content (UGC), online search traffic and offline light vehicle sales of different models.

512

Abstract

Purpose

This study explores the direct relationship between social media user-generated content (UGC), online search traffic and offline light vehicle sales of different models.

Design/methodology/approach

The long-run equilibrium relationship and short-run dynamic effects between the valence and volume of UGC, online search traffic and offline car sales are analyzed by applying the autoregressive distribution lag (ARDL) model.

Findings

The study found the following. (1) In the long-run relationship, the valence of online reviews on social media platforms is significantly negatively correlated with the sales of all models. However, in the short-run, the valence of online reviews has a significant positive correlation with all models in different lag periods. (2) The volume of online reviews is significantly positively correlated with the sales of all models in the long run. However, in the short run, the relationship between the volume of online reviews and the sales of lower-sales-volume cars is uncertain. There is a significant positive correlation between the volume of reviews and the sales of higher-sales-volume cars. (3) Online search traffic has a significantly negative correlation with the sales of all models in the long run. However, in the short run, there is no consistent conclusion on the relationship between online search traffic and car sales.

Originality/value

This study provides a reference for managers to use in their efforts to improve offline high-involvement product sales using online information.

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Article
Publication date: 25 July 2024

Shutian Wang, Yan Lin, Lu Yan and Guoqing Zhu

Online comments significantly impact consumer choice and product sales. Existing research focuses on the direct effects of online comments on product sales, whereas studies on the…

172

Abstract

Purpose

Online comments significantly impact consumer choice and product sales. Existing research focuses on the direct effects of online comments on product sales, whereas studies on the spillover effects of online comments are relatively limited, especially for high-involvement products. This study explores the impact of online comments of competing products on focal product sales in high-involvement products.

Design/methodology/approach

Data mining techniques are used to collect 72,367 online comments from the Autohome platform, and sentiment analysis algorithms are used to quantify the textual information for subsequent analysis. Specifically, two panel two-way fixed-effects models are constructed to explore the impact of the average valence and quantity of online comments of competing cars on focal car sales, and analyse this impact in terms of heterogeneity across car price levels, while the moderating effect of online comments of competing cars is explored.

Findings

The results show that the average quantity of online comments of competing cars has a significant effect on the sales of the focal car in the overall sample, while the average valence of online comments of competing cars does not have a significant spillover effect. Moreover, the spillover effect varies by car price level. For high-priced cars, the average quantity of online comments of competing cars significantly and negatively affects focal car sales, and the average valence of online comments of competing cars significantly and negatively moderates the effect of the valence of focal car online comments on its sales. For lower-priced cars, online comments of competing cars don’t significantly affect focal car sales.

Originality/value

This study not only enriches the theory of online comments and high-involvement product sales, but also provides reference and guidance for exploring spillover effects of online comments for other products.

Details

Industrial Management & Data Systems, vol. 124 no. 9
Type: Research Article
ISSN: 0263-5577

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