Challenges and drivers for data mining in the AEC sector. Issue 11 (2nd October 2018)
- Record Type:
- Journal Article
- Title:
- Challenges and drivers for data mining in the AEC sector. Issue 11 (2nd October 2018)
- Main Title:
- Challenges and drivers for data mining in the AEC sector
- Authors:
- Ahmed, Vian
Aziz, Zeeshan
Tezel, Algan
Riaz, Zainab - Abstract:
- Abstract : Purpose: The purpose of this paper is to explore the current challenges and drivers for data mining in the AEC sector. Design/methodology/approach: Following a comprehensive literature review, the data mining concept was investigated through a workshop with industry experts and academics. Findings: The results showed that the key drivers for using data mining within the AEC sector is associated with the sustainability, process improvement, market intelligence, cost certainty and cost reduction, performance certainty and decision support systems agendas in the sector. As for the processes with the greatest potential for data mining application, design, construction, procurement, forensic analysis, sustainability and energy consumption and reuse of digital components were perceived as the main process areas. While the key challenges were perceived as being, data issues due to the fragmented nature of the construction process, the need for a cultural change, IT systems used in silos, skills requirements and having clearly defined business goals. Originality/value: With the increasing abundance of data, business intelligence and analytics and its related concepts, data mining and Big Data have captured the attention of practitioners and academics for the last 20 years. On the other hand, and despite the growing amount of data in its business context, the AEC sector still lags behind in utilising those concepts in its end products and daily operations with limitedAbstract : Purpose: The purpose of this paper is to explore the current challenges and drivers for data mining in the AEC sector. Design/methodology/approach: Following a comprehensive literature review, the data mining concept was investigated through a workshop with industry experts and academics. Findings: The results showed that the key drivers for using data mining within the AEC sector is associated with the sustainability, process improvement, market intelligence, cost certainty and cost reduction, performance certainty and decision support systems agendas in the sector. As for the processes with the greatest potential for data mining application, design, construction, procurement, forensic analysis, sustainability and energy consumption and reuse of digital components were perceived as the main process areas. While the key challenges were perceived as being, data issues due to the fragmented nature of the construction process, the need for a cultural change, IT systems used in silos, skills requirements and having clearly defined business goals. Originality/value: With the increasing abundance of data, business intelligence and analytics and its related concepts, data mining and Big Data have captured the attention of practitioners and academics for the last 20 years. On the other hand, and despite the growing amount of data in its business context, the AEC sector still lags behind in utilising those concepts in its end products and daily operations with limited research conducted to explore those issues at the sector level. This paper investigates the main opportunities and barriers for data mining in the AEC sector with a practical focus. … (more)
- Is Part Of:
- Engineering, construction and architectural management. Volume 25:Issue 11(2018)
- Journal:
- Engineering, construction and architectural management
- Issue:
- Volume 25:Issue 11(2018)
- Issue Display:
- Volume 25, Issue 11 (2018)
- Year:
- 2018
- Volume:
- 25
- Issue:
- 11
- Issue Sort Value:
- 2018-0025-0011-0000
- Page Start:
- 1436
- Page End:
- 1453
- Publication Date:
- 2018-10-02
- Subjects:
- Technology -- Decision support systems -- Information and communication technology (ICT) applications
Construction industry -- Management -- Periodicals
Engineering -- Management -- Periodicals
Engineering -- Periodicals
Building -- Periodicals
624.068 - Journal URLs:
- http://www.emeraldinsight.com/journals.htm?issn=0969-9988 ↗
http://www.emeraldinsight.com/ ↗
http://www.blackwell-synergy.com/member/institutions/issuelist.asp?journal=eca ↗ - DOI:
- 10.1108/ECAM-01-2018-0035 ↗
- Languages:
- English
- ISSNs:
- 0969-9988
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3758.609000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 22227.xml