BIM and Big Data for Construction Cost Management

BIM and Big Data for Construction Cost Management

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Overview

This book is designed to help practitioners and students in a wide range of construction project management professions to understand what building information modelling (BIM) and big data could mean for them and how they should prepare to work successfully on BIM-compliant projects and maintain their competencies in this essential and expanding area.

In this book, the state-of-the-art information technologies that support high-profile BIM implementation are introduced, and case studies show how BIM has integrated core quantity surveying and cost management responsibilities and how big data can enable informed decision-making for cost control and cost planning. The authors' combined professional and academic experience demonstrates, with practical examples, the importance of using BIM and particularly the fusion of BIM and big data, to sharpen competitiveness in global and domestic markets.

This book is a highly valuable guide for people in a wide range of construction project management and quantity surveying roles. In addition, implications for project management, facilities management, contract administration, and dispute resolution are also explored through the case studies, making this book essential reading for built environment and engineering professionals.

Product Details

ISBN-13: 9781351172301
Publisher: CRC Press
Publication date: 10/11/2018
Sold by: Barnes & Noble
Format: NOOK Book
Pages: 156
File size: 5 MB

About the Author

Weisheng Lu is Associate Dean and Associate Professor, Department of Real Estate and Construction, Faculty of Architecture, Hong Kong University.

Chi Cheung Lai is a PRC Register Cost Engineer and Director at Northcroft Hong Kong Ltd.

Tung Tse PRC Register Cost Engineer at Northcroft Hong Kong Ltd.

Table of Contents

1. Introduction

2. BIM theories and empirics

3. BIM implementation strategies

4. Adopting BIM in quantity surveying

5. Big data for cost management

6. Case projects

7. Current challenges

8. Recommendable best practice

9. The future of BIM in quantity surveying

10. Conclusion

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