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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.

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.

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.

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.

  • Type: Journal Article
  • Keywords: Indonesia; Cost model; ANFIS; Multiple regression; Building project; Conceptual cost estimation;
  • ISBN/ISSN: 2044-124X
  • URL: https://doi.org/10.1108/BEPAM-11-2017-0111
  • Abstract:
    The purpose of this paper is to develop a conceptual cost estimation (CCE) model for building project by using a pragmatic approach, which is a mix of tools drawn from multiple regression analysis (MRA) and adaptive neuro-fuzzy inference system (ANFIS), to improve the accuracy of cost estimation at an early stage. Design/methodology/approach This paper presents a set of MRA and integrating MRA with ANFIS or MRANFIS. A simultaneous regression analysis was developed to determine the main cost factors from 12 variables as input variables in the ANFIS model. Cost data from 78 projects of state building in West Sumatra, Indonesia were used to indicate the advantages of the proposed model. Findings The result shows that the proposed model, MRANFIS, has successfully improved the mean absolute percent error (MAPE) by 2.8 percent from MRA of 10.7–7.9 percent for closeness of fit to the model data and by 3.1 percent from MRA of 9.8–6.7 percent for prediction performance to the new data. Research limitations/implications Because the significant variables are different for each building type, the model may be not appropriate for other buildings depending on the characteristics of building. The models can be used and analyzed based on the own historical project data for each case so that the model can be applied. Originality/value The study thus provides better accuracy of CCE at an early stage for state building projects in West Sumatra, Indonesia by using the integrated model of MRA and ANFIS.

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.

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.

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.