A contextual parsing of big data values to quantity surveyors

Zafira Nadia Maaz, Shamsulhadi Bandi, Roslan Amirudin


Big data is the new generation of technology designed for organizations to economically extract value from large volumes of a wide variety of data through high velocity capture, discovery, storage and analysis. Manifest as the frontier of 21st century technology, big data instigate superior business return. This lure businesses to zealously capitalize big data. In correspond, professionals too are charting their way to improve customer value with big data. Leading research in this area accede maximization on big data; revolutionized the norm of medical and accounting profession. Despite the substantial value, big data uptake from the quantity surveying profession recognized subtle. Contrarily, construction stakeholders swiftly embrace modern technology in their construction value chain. This invoke a change in data landscape thus, present an urgent call for professionals, especially quantity surveyors to recognize the change, embrace and reap the big data benefit. This paper aims to expand big data knowledge from the context of quantity surveying profession as an approach to soothe the big data and quantity surveying gap. This paper identifies generic big data value from professional perspective and explore big data value from the quantity surveying context. Aligning to the blurry big data paradigm in the quantity surveying context, this research adopts quantitative research with desk study on 28 papers and framework analysis through 15 semi-structured interviews with big data industry expert with quantity surveying background. This research found that big data values are consistent across profession albeit the difference on how big data is maximized. Other than that, the paucity of quantity surveying big data pursuance seen as repercussion of infancy big data state in the construction industry. However, this research insinuate quantity surveying profession are in strategic position to move forward with big data.


Big data; Big data value; Construction Industry; Framework Analysis; Quantity Surveyors

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DOI: https://doi.org/10.11113/ijbes.v5.n3.311


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