Adoption of the big data concept in the construction industry

Reyes Veras, P (2023) Adoption of the big data concept in the construction industry. PhD thesis, University of Wolverhampton, UK.

Abstract

The Big Data (BD) boom has increased exponentially in recent years, reaching even the most traditional industries. In construction, the migration towards sustainability and new technologies that produce user and environmentally friendly projects is now a requirement in almost every country. Meanwhile, BD technology has become a possible solution to the challenges that the industry faces nowadays with some authors naming this technology as the future of construction. However, despite this reception, studies that explain in detail the factors that favour the adoption of BD are scarce or non-existent and the adoption itself has proven to be a challenge, especially in industries such as construction that are not technology driven. Understanding the critical factors that influence BD adoption has become the focus of many industries that seek to exploit the benefits offered by this technology. Therefore, the aim of this research is to explore the adoption of BD in the construction industry. First, the awareness of the Dominican Republic's construction industry on the BD concept, its characteristics, and benefits was assessed. The key drivers, strategies, and challenges regarding the adoption of BD in the industry were also investigated. A qualitative method was selected to identify these strategies due to the lack of maturity and the scarcity of sources that address the subject. Semi-structured interviews were selected as the data collection tool, and content and thematic analysis were chosen to acquire an in-depth knowledge of the interviews. Endsley's model of situational awareness was adapted to provide a better understanding of the industry's awareness of BD. The sampling technique adopted was non-probabilistic due to some of the specific criteria identified during the secondary data collection process. In the data collection process, 21 interviews were conducted with representatives of 19 organisations with an undoubted presence in the construction market of the Dominican Republic. The results showed that there is an overall basic level of awareness about BD in the construction industry of the Dominican Republic. Moreover, nine key drivers for BD adoption were identified and grouped into internal and external drivers. Additionally, four main strategies or central policies for adopting the technology and seven main challenges were identified. These findings were used to develop an organisation readiness assessment tool and a strategic framework for BD adoption in the construction industry. This study concluded that new technologies such as Big Data (BD) require a change in the industry's culture and the adoption of digital approaches to be fully implemented. The findings of this research provide valuable insights that can help the construction industry adopt BD technology, thus accessing the short and long-term benefits that this technology offers.

Item Type: Thesis (Doctoral)
Thesis advisor: Suresh, S
Uncontrolled Keywords: culture; market; sustainability; migration; thematic analysis; Dominican Republic; interview
Index terms: presence, sampling, readiness assessment, construction industry, construction market, environmentally friendly, new technology, migration, secondary data, critical factor, thematic analysis, Dominican Republic, interview, big data, face, strategy, qualitative method
Subjects: market analysis, demography, Geography, sustainable design, environmental science, innovation and technology management, psychology, information systems, industry analysis, methods and analysis, management, research design and methodology, risk assessment, data collection methods
Topics: Business Strategy, Research Practice, Organizational Design, Urban Studies, Digital Applications, Risk Management, Sustainability, Geographical Context, Engineering Principles
Descriptive scope: 5 PCTEA

N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here