斯里兰卡建筑业的大数据分析:挑战与策略评估

A. Atapattu, R. M. Wattuhewa, K. Waidyasekara, R. Dilakshan
{"title":"斯里兰卡建筑业的大数据分析:挑战与策略评估","authors":"A. Atapattu, R. M. Wattuhewa, K. Waidyasekara, R. Dilakshan","doi":"10.31705/wcs.2023.24","DOIUrl":null,"url":null,"abstract":"The increasing complexity of construction projects and the expansion of the construction sector has complicated the data management process by highlighting the need for proper data management tools in arranging and organising construction data. Specifically, countries with developing economies such as Sri Lanka require more advanced data management tools, since the construction sector is the backbone of their economies. In this context, this study aims to identify the challenges to the implementation of Big Data Analytics (BDA) in the Sri Lankan construction sector and the potential strategies which can be adopted in overcoming the challenges for the implementation. Accordingly, a qualitative approach was followed in achieving the aim of the study. A comprehensive literature review was conducted to identify the existing body of knowledge related to the study area. Twelve semi-structured interviews were conducted for primary data collection with experts in the fields of construction and data analytics and the non-probability purposive sampling technique was used to select the experts for the data collection. Data were analysed using the content analysis method. Findings revealed that the requirement of large capital expenditure, resistance from industry professionals and lack of industry awareness are the major barriers to adopting BDA in the Sri Lankan construction sector. Eventually, it was revealed that conducting awareness sessions and educating the industry stakeholders will assist the strategic implementation of BDA in the Sri Lankan construction sector.","PeriodicalId":221447,"journal":{"name":"11th World Construction Symposium - 2023","volume":" 16","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Big data analytics in the Sri Lankan construction industry: an assessment of the challenges and strategies\",\"authors\":\"A. Atapattu, R. M. Wattuhewa, K. Waidyasekara, R. Dilakshan\",\"doi\":\"10.31705/wcs.2023.24\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The increasing complexity of construction projects and the expansion of the construction sector has complicated the data management process by highlighting the need for proper data management tools in arranging and organising construction data. Specifically, countries with developing economies such as Sri Lanka require more advanced data management tools, since the construction sector is the backbone of their economies. In this context, this study aims to identify the challenges to the implementation of Big Data Analytics (BDA) in the Sri Lankan construction sector and the potential strategies which can be adopted in overcoming the challenges for the implementation. Accordingly, a qualitative approach was followed in achieving the aim of the study. A comprehensive literature review was conducted to identify the existing body of knowledge related to the study area. Twelve semi-structured interviews were conducted for primary data collection with experts in the fields of construction and data analytics and the non-probability purposive sampling technique was used to select the experts for the data collection. Data were analysed using the content analysis method. Findings revealed that the requirement of large capital expenditure, resistance from industry professionals and lack of industry awareness are the major barriers to adopting BDA in the Sri Lankan construction sector. Eventually, it was revealed that conducting awareness sessions and educating the industry stakeholders will assist the strategic implementation of BDA in the Sri Lankan construction sector.\",\"PeriodicalId\":221447,\"journal\":{\"name\":\"11th World Construction Symposium - 2023\",\"volume\":\" 16\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"11th World Construction Symposium - 2023\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.31705/wcs.2023.24\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"11th World Construction Symposium - 2023","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31705/wcs.2023.24","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

随着建筑项目的日益复杂和建筑行业的扩张,在安排和组织建筑数据时需要适当的数据管理工具,这使得数据管理过程变得复杂。具体来说,斯里兰卡等发展中国家需要更先进的数据管理工具,因为建筑业是这些国家经济的支柱。在此背景下,本研究旨在确定在斯里兰卡建筑部门实施大数据分析(BDA)的挑战,以及在克服实施挑战时可以采用的潜在策略。因此,为了达到研究的目的,采用了定性方法。我们进行了全面的文献综述,以确定与研究领域相关的现有知识体系。对建筑和数据分析领域的专家进行了12次半结构化访谈,进行了初步数据收集,并采用非概率有目的抽样技术选择专家进行数据收集。采用内容分析法对资料进行分析。调查结果显示,大量资本支出的要求,来自行业专业人士的抵制和缺乏行业意识是斯里兰卡建筑业采用BDA的主要障碍。最后,据透露,开展认识会议和教育行业利益相关者将有助于在斯里兰卡建筑部门战略实施BDA。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Big data analytics in the Sri Lankan construction industry: an assessment of the challenges and strategies
The increasing complexity of construction projects and the expansion of the construction sector has complicated the data management process by highlighting the need for proper data management tools in arranging and organising construction data. Specifically, countries with developing economies such as Sri Lanka require more advanced data management tools, since the construction sector is the backbone of their economies. In this context, this study aims to identify the challenges to the implementation of Big Data Analytics (BDA) in the Sri Lankan construction sector and the potential strategies which can be adopted in overcoming the challenges for the implementation. Accordingly, a qualitative approach was followed in achieving the aim of the study. A comprehensive literature review was conducted to identify the existing body of knowledge related to the study area. Twelve semi-structured interviews were conducted for primary data collection with experts in the fields of construction and data analytics and the non-probability purposive sampling technique was used to select the experts for the data collection. Data were analysed using the content analysis method. Findings revealed that the requirement of large capital expenditure, resistance from industry professionals and lack of industry awareness are the major barriers to adopting BDA in the Sri Lankan construction sector. Eventually, it was revealed that conducting awareness sessions and educating the industry stakeholders will assist the strategic implementation of BDA in the Sri Lankan construction sector.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
0.40
自引率
0.00%
发文量
0
期刊最新文献
Economic models of climate change: systematic review of benefits, limitations, and future directions Adaptation of blockchain and smart contracts to the construction industry of developing countries A Taxonomy of waterproofing systems for high-rise building projects in the tropics Potential use of digital twin for construction progress monitoring Adoptability of bioplastic as a sustainable material in Sri Lankan building construction industry
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1