Data Monetization Strategies: The Construction Industry Market Analysis (International Journal of Built Environment and Sustainability, 2024)
Data monetization is leveraging data to obtain economic benefits. In the context of Big Data Analytics (BDA), data serves as a fundamental asset, enabling the transformation into valuable insights throughout various construction phases. Unfortunately, there is lack of studies focusing on data monetization within the construction industry, given the unique supply and demand characteristics among construction stakeholders. This study aims to address the objective of identifying data monetization strategies applicable to the construction industry, particularly for data sellers and data buyers. Data was gathered through a quantitative survey among 100 construction practitioners in Malaysia, encompassing developers, contractors, consultants, government agencies, technology providers, and academia. Respondents were further categorized into data sellers and data buyers. The data were analyzed using mean analysis, t-test and Spearman's rank correlation coefficient. The study identified six data monetization strategies, comprising 19 determinants. The analysis revealed high preference on all data monetization strategies and moderate differences in the preferred strategies between data sellers and buyers. Significant differences were found in 3 determinants which are (1) trading data to facilitate decision-making, (2) trading data for construction reports, benchmarks, and indices, and (3) selling visualized data on real-time platforms. The t-test indicated that data sellers are more inclined towards the three strategies for effective monetization. Furthermore, Spearman’s correlation coefficient revealed the 3 determinants also positively influence another 3 determinants of (1) data wrapping to reflect better service from data provider, (2) buying raw data with its inherit information and (3) monetizing internal data to optimize organization’s work process. The insights enable stakeholders to implement mechanisms that foster data monetization within project cultures accelerating BDA undertakings. Future recommendations include using larger sample sizes to enhance generalizability and to explore more areas such as construction contracts, cost, health, and safety.
Keywords: Big Data Analytics, Data Monetization, Construction Project Management, Construction IT