{"title":"多米尼加共和国建筑业采用大数据的主要驱动因素:一项实证研究","authors":"Paola Reyes-Veras, Suresh Renukappa, Subashini Suresh","doi":"10.1680/jensu.21.00067","DOIUrl":null,"url":null,"abstract":"Construction methods have barely changed since the last industrial revolution, but new project requirements are subject to change every day. Including sustainability and new technologies that produce user and environmentally friendly projects is now a requirement in almost every country. Big data (BD) are mainly characterised by improving the decision making process through data analysis. Adopting BD in the construction industry is expected to impact efficiency positively in design and construction activities. However, it requires a change in the industry’s culture and the adoption of digital approaches to be implemented fully. This paper addresses the key drivers for the adoption of BD in the construction industry of the Dominican Republic. Qualitative research was implemented to explore the topic due to the scarce information available. Twenty-one semi-structured interviews were analysed using thematic analysis. In some cases, the participants provided their points of view based on their experience with similar technologies such as building information modelling and ‘Internet of things’. The data analysis identified nine critical drivers, classified as internal and external. The internal drivers are knowledge of BD benefits to the organisation, impact on competitiveness, technology awareness, solution to company’s needs, organisation’s technology-driven culture and client’s requirements. Similarly, the internal drivers are industry motivation, regulatory framework and technology change adaptability. This paper sheds light on the motivations behind adopting BD and helps understand the industry’s needs. It also delivers evidence on the need for improved training for present and future professionals focused on developing digital skills.","PeriodicalId":49671,"journal":{"name":"Proceedings of the Institution of Civil Engineers-Engineering Sustainability","volume":"97 4","pages":"0"},"PeriodicalIF":1.5000,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Key drivers for Big Data adoption in the Dominican Republic construction industry: an empirical study\",\"authors\":\"Paola Reyes-Veras, Suresh Renukappa, Subashini Suresh\",\"doi\":\"10.1680/jensu.21.00067\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Construction methods have barely changed since the last industrial revolution, but new project requirements are subject to change every day. Including sustainability and new technologies that produce user and environmentally friendly projects is now a requirement in almost every country. Big data (BD) are mainly characterised by improving the decision making process through data analysis. Adopting BD in the construction industry is expected to impact efficiency positively in design and construction activities. However, it requires a change in the industry’s culture and the adoption of digital approaches to be implemented fully. This paper addresses the key drivers for the adoption of BD in the construction industry of the Dominican Republic. Qualitative research was implemented to explore the topic due to the scarce information available. Twenty-one semi-structured interviews were analysed using thematic analysis. In some cases, the participants provided their points of view based on their experience with similar technologies such as building information modelling and ‘Internet of things’. The data analysis identified nine critical drivers, classified as internal and external. The internal drivers are knowledge of BD benefits to the organisation, impact on competitiveness, technology awareness, solution to company’s needs, organisation’s technology-driven culture and client’s requirements. Similarly, the internal drivers are industry motivation, regulatory framework and technology change adaptability. This paper sheds light on the motivations behind adopting BD and helps understand the industry’s needs. It also delivers evidence on the need for improved training for present and future professionals focused on developing digital skills.\",\"PeriodicalId\":49671,\"journal\":{\"name\":\"Proceedings of the Institution of Civil Engineers-Engineering Sustainability\",\"volume\":\"97 4\",\"pages\":\"0\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2023-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Institution of Civil Engineers-Engineering Sustainability\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1680/jensu.21.00067\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Institution of Civil Engineers-Engineering Sustainability","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1680/jensu.21.00067","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
Key drivers for Big Data adoption in the Dominican Republic construction industry: an empirical study
Construction methods have barely changed since the last industrial revolution, but new project requirements are subject to change every day. Including sustainability and new technologies that produce user and environmentally friendly projects is now a requirement in almost every country. Big data (BD) are mainly characterised by improving the decision making process through data analysis. Adopting BD in the construction industry is expected to impact efficiency positively in design and construction activities. However, it requires a change in the industry’s culture and the adoption of digital approaches to be implemented fully. This paper addresses the key drivers for the adoption of BD in the construction industry of the Dominican Republic. Qualitative research was implemented to explore the topic due to the scarce information available. Twenty-one semi-structured interviews were analysed using thematic analysis. In some cases, the participants provided their points of view based on their experience with similar technologies such as building information modelling and ‘Internet of things’. The data analysis identified nine critical drivers, classified as internal and external. The internal drivers are knowledge of BD benefits to the organisation, impact on competitiveness, technology awareness, solution to company’s needs, organisation’s technology-driven culture and client’s requirements. Similarly, the internal drivers are industry motivation, regulatory framework and technology change adaptability. This paper sheds light on the motivations behind adopting BD and helps understand the industry’s needs. It also delivers evidence on the need for improved training for present and future professionals focused on developing digital skills.
期刊介绍:
Engineering Sustainability provides a forum for sharing the latest thinking from research and practice, and increasingly is presenting the ''how to'' of engineering a resilient future. The journal features refereed papers and shorter articles relating to the pursuit and implementation of sustainability principles through engineering planning, design and application. The tensions between and integration of social, economic and environmental considerations within such schemes are of particular relevance. Methodologies for assessing sustainability, policy issues, education and corporate responsibility will also be included. The aims will be met primarily by providing papers and briefing notes (including case histories and best practice guidance) of use to decision-makers, practitioners, researchers and students.