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Abd Jamil, A H and Fathi, M S (2018) Contractual challenges for BIM-based construction projects: a systematic review. Built Environment Project and Asset Management, 8(04), 372–85.

Adefila, A, Abuzeinab, A, Whitehead, T and Oyinlola, M (2020) Bottle house: utilising appreciative inquiry to develop a user acceptance model. Built Environment Project and Asset Management, 10(04), 567–83.

Al-Gahtani, K, Alsulaihi, I, Ali, M and Marzouk, M (2017) Production of green concrete using recycled waste aggregate and byproducts. Built Environment Project and Asset Management, 7(04), 413-25.

Amadi, C, Carrillo, P and Tuuli, M (2018) Stakeholder management in PPP projects: external stakeholders’ perspective. Built Environment Project and Asset Management, 8(04), 403–14.

Carrière, S, Weigend Rodríguez, R, Pey, P, Pomponi, F and Ramakrishna, S (2020) Circular cities: the case of Singapore. Built Environment Project and Asset Management, 10(04), 491–507.

Crippa, J, Araujo, A M, Bem, D, Ugaya, C M and Scheer, S (2020) A systematic review of BIM usage for life cycle impact assessment. Built Environment Project and Asset Management, 10(04), 603–18.

Farghaly, K, Abanda, F, Vidalakis, C and Wood, G (2019) BIM-linked data integration for asset management. Built Environment Project and Asset Management, 9(04), 489–502.

Hadiwattege, C, Senaratne, S, Sandanayake, Y and Fernando, N G (2018) Academic research in emerging knowledge-based economies. Built Environment Project and Asset Management, 8(04), 415–28.

Hettige, N, Perera, B A K S and Mallawaarachchi, H (2017) A framework for adopting green leasing in developing countries: The case of Sri Lanka. Built Environment Project and Asset Management, 7(04), 377-87.

Ikediashi, D I, Ogunlana, S O and Odesola, I A (2015) Service quality and user satisfaction of outsourced facilities management services in Nigeria’s public hospitals. Built Environment Project and Asset Management, 5(04), 363-79.

Jafari, A and Akhavian, R (2019) Driving forces for the US residential housing price: a predictive analysis. Built Environment Project and Asset Management, 9(04), 515–29.

Jumas, D, Mohd-Rahim, F A, Zainon, N and Utama, W P (2018) Improving accuracy of conceptual cost estimation using MRA and ANFIS in Indonesian building projects. Built Environment Project and Asset Management, 8(04), 348–57.

Khallaf, R, Naderpajouh, N and Hastak, M (2018) A systematic approach to develop risk registry frameworks for complex projects. Built Environment Project and Asset Management, 8(04), 334–47.

Kim, K P and Park, K S (2016) Primary BIM dataset for refurbishing flood risk vulnerable housing in the UK. Built Environment Project and Asset Management, 6(04), 365-78.

Kumaraswamy, M, Wong, K K W and Chung, J (2017) Focusing megaproject strategies on sustainable best value of stakeholders. Built Environment Project and Asset Management, 7(04), 441-55.

Liu, C and Li, Y (2016) Measuring eco-roof mitigation on flash floods via gis simulation. Built Environment Project and Asset Management, 6(04), 415-27.

Madanayake, U H and Egbu, C (2019) Critical analysis for big data studies in construction: significant gaps in knowledge. Built Environment Project and Asset Management, 9(04), 530–47.

  • Type: Journal Article
  • Keywords: Construction industry; Built environment; Systematic review; Data analysis; Big data analytics; Knowledge gaps;
  • ISBN/ISSN: 2044-124X
  • URL: https://doi.org/10.1108/BEPAM-04-2018-0074
  • Abstract:
    The purpose of this paper is to identify the gaps and potential future research avenues in the big data research specifically in the construction industry. Design/methodology/approach The paper adopts systematic literature review (SLR) approach to observe and understand trends and extant patterns/themes in the big data analytics (BDA) research area particularly in construction-specific literature. Findings A significant rise in construction big data research is identified with an increasing trend in number of yearly articles. The main themes discussed were big data as a concept, big data analytical methods/techniques, big data opportunities – challenges and big data application. The paper emphasises “the implication of big data in to overall sustainability” as a gap that needs to be addressed. These implications are categorised as social, economic and environmental aspects. Research limitations/implications The SLR is carried out for construction technology and management research for the time period of 2007–2017 in Scopus and emerald databases only. Practical implications The paper enables practitioners to explore the key themes discussed around big data research as well as the practical applicability of big data techniques. The advances in existing big data research inform practitioners the current social, economic and environmental implications of big data which would ultimately help them to incorporate into their strategies to pursue competitive advantage. Identification of knowledge gaps helps keep the academic research move forward for a continuously evolving body of knowledge. The suggested new research avenues will inform future researchers for potential trending and untouched areas for research. Social implications Identification of knowledge gaps helps keep the academic research move forward for continuous improvement while learning. The continuously evolving body of knowledge is an asset to the society in terms of revealing the truth about emerging technologies. Originality/value There is currently no comprehensive review that addresses social, economic and environmental implications of big data in construction literature. Through this paper, these gaps are identified and filled in an understandable way. This paper establishes these gaps as key issues to consider for the continuous future improvement of big data research in the context of the construction industry.

Manu, P, Mahamadu, A, Booth, C, Olomolaiye, P, Ibrahim, A D and Coker, A (2018) Assessment of procurement capacity challenges inhibiting public infrastructure procurement. Built Environment Project and Asset Management, 8(04), 386–402.

Marzouk, M and Enaba, M (2019) Analyzing project data in BIM with descriptive analytics to improve project performance. Built Environment Project and Asset Management, 9(04), 476–88.

Mitra, A and Munir, K (2019) Influence of Big Data in managing cyber assets. Built Environment Project and Asset Management, 9(04), 503–14.

Nguyen, T P and Chileshe, N (2015) Revisiting the construction project failure factors in Vietnam. Built Environment Project and Asset Management, 5(04), 398-416.

Nielsen, L-H K, Akanmu, A and Anumba, C J (2015) Comparative analysis of back-to-back subcontracts in the construction and telecommunications industries. Built Environment Project and Asset Management, 5(04), 446-60.

Ofori-Boadu, A N, Shofoluwe, M A, Owusu-Manu, D-G, Holt, G D and Edwards, D (2015) Analysis of US commercial buildings’ energy efficiency programs. Built Environment Project and Asset Management, 5(04), 349-62.

Okorafor, C, Emuze, F, Das, D, Awuzie, B O and Haupt, T (2020) An artefact for improving the delivery of building energy retrofit project in South Africa. Built Environment Project and Asset Management, 10(04), 619–35.

Olatunji, O A, Orundami, A O and Ogundare, O (2018) Causal relationship between material price fluctuation and project’s outturn costs. Built Environment Project and Asset Management, 8(04), 358–71.

Omotayo, T, Olanipekun, A, Obi, L and Boateng, P (2020) A systems thinking approach for incremental reduction of non-physical waste. Built Environment Project and Asset Management, 10(04), 509–28.

Osunsanmi, T O, Aigbavboa, C O, Emmanuel Oke, A and Liphadzi, M (2020) Appraisal of stakeholders' willingness to adopt construction 4.0 technologies for construction projects. Built Environment Project and Asset Management, 10(04), 547–65.

Oyewobi, L O, Windapo, A O and James, R O B (2015) An empirical analysis of construction organisations’ competitive strategies and performance. Built Environment Project and Asset Management, 5(04), 417-31.

Ozcan, D G (2017) An analytic network process model to examine LEED-certified buildings’ operational performance. Built Environment Project and Asset Management, 7(04), 366-76.

Pathirage, C and Al-Khaili, K (2016) Disaster vulnerability of Emirati energy sector and barriers to enhance resilience. Built Environment Project and Asset Management, 6(04), 403-14.

Ram, J, Afridi, N K and Khan, K A (2019) Adoption of Big Data analytics in construction: development of a conceptual model. Built Environment Project and Asset Management, 9(04), 564–79.

Rose, J and Jayawickrama, J (2016) Capacity building of institutions for disaster risk reduction: Learning from communities as first responders. Built Environment Project and Asset Management, 6(04), 391-402.

Seneviratne, K, Amaratunga, D and Haigh, R (2015) Post-conflict housing reconstruction: Exploring the challenges of addressing housing needs in Sri Lanka. Built Environment Project and Asset Management, 5(04), 432-45.

Waidyasekara, K G A S, De Silva, L and Rameezdeen, R (2017) Application of “r” principles to enhance the efficiency of water usage in construction sites. Built Environment Project and Asset Management, 7(04), 400-12.

Walimuni, P C, Samaraweera, A and De Silva, L (2017) Payment mechanisms for contractors for better environmental hazard controlling in road construction projects. Built Environment Project and Asset Management, 7(04), 426-40.

Wedawatta, G and Ingirige, B (2016) A conceptual framework for understanding resilience of construction SMEs to extreme weather events. Built Environment Project and Asset Management, 6(04), 428-43.

Wedawatta, G, Kulatunga, U, Amaratunga, D and Parvez, A (2016) Disaster risk reduction infrastructure requirements for south-western Bangladesh: Perspectives of local communities. Built Environment Project and Asset Management, 6(04), 379-90.

Weigend Rodríguez, R, Pomponi, F, Webster, K and D'Amico, B (2020) The future of the circular economy and the circular economy of the future. Built Environment Project and Asset Management, 10(04), 529–46.

Windapo, A O and Moghayedi, A (2020) Adoption of smart technologies and circular economy performance of buildings. Built Environment Project and Asset Management, 10(04), 585–601.

Yap, J Y L, Ho, C C and Ting, C (2019) A systematic review of the applications of multi-criteria decision-making methods in site selection problems. Built Environment Project and Asset Management, 9(04), 548–63.

Zeb, J (2017) An eco asset ontology towards effective eco asset management. Built Environment Project and Asset Management, 7(04), 388-99.

Zeb, J, Froese, T and Vanier, D (2015) An ontology-supported asset information integrator system in infrastructure management. Built Environment Project and Asset Management, 5(04), 380-97.

Zhao, X and Pan, W (2017) Co-productive interrelations between business model and zero-carbon building: A conceptual model. Built Environment Project and Asset Management, 7(04), 353-65.