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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.

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.

• Type: Journal Article
• Keywords: 4IR; Building maintenance; Building performance; Circular economy; Facility management; Management decision time; Smart technologies; Energy and water consumption;
• ISBN/ISSN: 2044-124X
• URL: https://doi.org/10.1108/BEPAM-04-2019-0041
• Abstract:
  This paper examines the use of intelligent technologies in buildings and whether the use of smart technologies impacts the circular economy performance of buildings in terms of energy and water consumption, their marginal cost and the management decision time and quality, for building management companies. The study is initiated through the detailed build-up of the proposition that employs a systematic literature review and adopts the case study research design to make a cross-case analysis of the information extracted from data. The data are derived from the operating costs of two buildings in which most advanced smart technologies are used in Cape Town and interviews with their facility managers. These data provide two research case studies. The results of the investigation are then analysed and linked back to the literature. The results of the research suggest that the implementation of smart technologies to create intelligent infrastructure is beneficial to the circular economy performance of buildings and the time taken for management decisions. The results of the study have proven that the impact of smart technologies on the circular economy performance of buildings is positive, as it lowers the cost of utilities and decreases the time required for management decisions. The research reported in this paper is exploratory, and due to its limited sample size, its findings may not be statistically generalizable to the population of high-occupancy buildings in Cape Town, which incorporate smart infrastructure technologies within their building management systems (BMSs). Also, the empirical data collected were limited to the views and opinions of the interviewees, and the secondary data were obtained from the selected buildings. The findings suggest that investment in smart technologies within buildings is of significant value and will improve the circular economy performance of buildings in terms of low energy and water use, and effective management decisions. The results imply that there would be more effective maintenance decisions taken by facilities managers, which will enable the maintenance of equipment to be properly monitored, problems with the building services and equipment to be identified in good time and in improved well-being and user satisfaction. The study provides evidence to support the concept that advanced smart technologies boost performance, the time required for management decisions and that they enable circularity in buildings. It supports the proposition that investment in the more advanced smart technologies in buildings has more positive rewards.

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.