Abstract
With constant flow of large data sets generated by different organisations, big data analytics promises to be a revolutionary game changer for Architecture, Engineering and Construction (AEC) industry. Despite the potential of Big Data, there has been little research conducted thus far to understand the Big Data phenomenon, specifically in the AEC industry. The objective of this research therefore is to understand the contributing factors for adopting big data in AEC firms. The investigation combined the perceived strategic value of BDA with the TOE framework (technology, organization, and environment), to develop and test a holistic model on big data adoption. A set of hypotheses derived from the extant literature was tested on data from structured surveys of about 365 firms, categorised as construction service firms (engineering and architecture) and construction firms (firms engaged in managing construction projects). The results indicated that the inhibitors and facilitators of BDA adoption are different in the construction services (architecture and engineering) and construction firms. For effective adoption of BDA solutions, the findings will guide the business managers to have realistic expectations of BDA integration challenges in AEC sector.
Highlights
As strategic emphasis on data-driven decision-making and innovation increases, firms today cannot afford to ignore the rewards of data science and advanced analytics for real-time insights of customers and machines by a big data application (BDA)-driven environment
Partial least square (PLS) was employed as a tool for measurement and structural analysis as it overcome the limitation of Exploratory factor analysis (EFA) analysis and several researchers in business, management and information systems field has recognized as an effective analytical method for measuring construct reliability and validity and model testing (Hair, et al, 2012)
The outcomes of our analysis indicated that the inhibitors and facilitators of BDA adoption intention were different in construction service firm’s vis a vis construction firms
Summary
As strategic emphasis on data-driven decision-making and innovation increases, firms today cannot afford to ignore the rewards of data science and advanced analytics for real-time insights of customers and machines by a big data application (BDA)-driven environment. With major economic development and urbanisation in progress, India is estimated to annually build 700–900 million square meters of residential and commercial space, till about 2020 (McKinsey, 2010). With such anticipated volume of construction, the Indian Architecture, Engineering and Construction (AEC) sector is certainly going to play a significant role in contributing to the Indian economy (Ahmed, et al, 2017). BDA implementation requires major modifications in the existing business processes to enable willing organisations to adapt, while looking to match the capabilities of their current system (Wang, et al, 2016a; Chaurasia and Rosin, 2017; Wang, et al, 2018b)
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