IDEAS home Printed from https://ideas.repec.org/a/vrs/otamic/v15y2023i1p192-212n14.html
   My bibliography  Save this article

Estimation of ideal construction duration in tender preparation stage for housing projects

Author

Listed:
  • Tirataci Hakan

    (Department of Architecture, Faculty of Architecture, Istanbul Technical University, Istanbul, Turkey hakantirataci@gmail.com)

  • Yaman Hakan

    (Department of Architecture, Faculty of Architecture, Istanbul Technical University, Istanbul, Turkey)

Abstract

Despite the potential of various methods for calculating construction duration, few studies have focused on the application of these methods in the tender preparation stage, and even fewer have focused on their application in public housing projects. Moreover, research related to construction duration in Turkey has indicated that considerable delays occur in public housing projects. Therefore, we investigated the factors affecting the construction duration of housing projects and developed a novel calculation method for estimating the ideal construction duration. Data on public housing projects were obtained from a major Turkish construction authority. Statistical data analysis was performed using multiple linear regression analysis, chi-squared automatic interaction detection (CHAID), and classification and regression tree (CART) methods. The results revealed that several factors significantly affected the ideal construction duration for each statistical method. The cutoffs and standard errors were calculated to test the validity of all three statistical methods. The regression formula indicated statistical significance when the calculation method was tested. The implementation of the methods for other public housing projects significantly reduced the number of delayed projects. The findings of this study are expected to contribute by way of enabling senior project managers to estimate the ideal construction duration for housing projects during the tender preparation stage.

Suggested Citation

  • Tirataci Hakan & Yaman Hakan, 2023. "Estimation of ideal construction duration in tender preparation stage for housing projects," Organization, Technology and Management in Construction, Sciendo, vol. 15(1), pages 192-212, January.
    • Handle: RePEc:vrs:otamic:v:15:y:2023:i:1:p:192-212:n:14
    DOI: 10.2478/otmcj-2023-0014
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/otmcj-2023-0014
    Download Restriction: no
    File URL: https://libkey.io/10.2478/otmcj-2023-0014?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Ruqaya Al-Sabah & Carol C. Menassa & Awad Hanna, 2014. "Evaluating impact of construction risks in the Arabian Gulf Region from perspective of multinational architecture, engineering and construction firms," Construction Management and Economics, Taylor & Francis Journals, vol. 32(4), pages 382-402, April.
    2. Mohammed Al-Khalil & Mohammed Al-Ghafly, 1999. "Important causes of delay in public utility projects in Saudi Arabia," Construction Management and Economics, Taylor & Francis Journals, vol. 17(5), pages 647-655.
    3. Hemanta Doloi & Anil Sawhney & K.C. Iyer, 2012. "Structural equation model for investigating factors affecting delay in Indian construction projects," Construction Management and Economics, Taylor & Francis Journals, vol. 30(10), pages 869-884, October.
    4. P. A. Koushki & K. Al-Rashid & N. Kartam, 2005. "Delays and cost increases in the construction of private residential projects in Kuwait," Construction Management and Economics, Taylor & Francis Journals, vol. 23(3), pages 285-294.
    5. Arjan Walraven & Bauke de Vries, 2009. "From demand driven contractor selection towards value driven contractor selection," Construction Management and Economics, Taylor & Francis Journals, vol. 27(6), pages 597-604.
    6. Fu, Chong Yau, 2004. "Combining loglinear model with classification and regression tree (CART): an application to birth data," Computational Statistics & Data Analysis, Elsevier, vol. 45(4), pages 865-874, May.
    7. Abdulrahman Salem Bageis & Chris Fortune, 2009. "Factors affecting the bid/no bid decision in the Saudi Arabian construction contractors," Construction Management and Economics, Taylor & Francis Journals, vol. 27(1), pages 53-71.
    8. Patricia M. Hillebrandt, 2000. "Economic Theory and the Construction Industry," Palgrave Macmillan Books, Palgrave Macmillan, edition 0, number 978-0-230-37248-1.
    9. Geng, Ruibin & Bose, Indranil & Chen, Xi, 2015. "Prediction of financial distress: An empirical study of listed Chinese companies using data mining," European Journal of Operational Research, Elsevier, vol. 241(1), pages 236-247.
    10. Curt Hagquist & Magnus Stenbeck, 1998. "Goodness of Fit in Regression Analysis – R 2 and G 2 Reconsidered," Quality & Quantity: International Journal of Methodology, Springer, vol. 32(3), pages 229-245, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mohammad Ajmal Nikjow & Li Liang & Xijing Qi & Samad M. E. Sepasgozar & Nicholas Chileshe, 2021. "Triggers of Delays in International Projects Using Engineering Procurement and Construction Delivery Methods in the Belt and Road Initiative: Case Study of a High-Speed Railway Projects," Sustainability, MDPI, vol. 13(17), pages 1-21, August.
    2. Goutom K. Pall & Adrian J. Bridge & Jason Gray & Martin Skitmore, 2019. "Causes of Delay in Power Transmission Projects: An Empirical Study," Energies, MDPI, vol. 13(1), pages 1-29, December.
    3. Li, Chunyu & Lou, Chenxin & Luo, Dan & Xing, Kai, 2021. "Chinese corporate distress prediction using LASSO: The role of earnings management," International Review of Financial Analysis, Elsevier, vol. 76(C).
    4. Basem Al Khatib & Yap Soon Poh & Ahmed El-Shafie, 2018. "Delay Factors in Reconstruction Projects: A Case Study of Mataf Expansion Project," Sustainability, MDPI, vol. 10(12), pages 1-18, December.
    5. Herve Kabanda & Alex Romard & Fuze Yurtsever & Anjali Wadhera & Joshua Andrews & Craig Merrett, 2021. "Construction Time Estimation Function for Canadian Utility Scale Power Plants," Energies, MDPI, vol. 14(17), pages 1-16, August.
    6. Ferda Halicioglu, 2007. "The demand for new housing in Turkey: an application of ARDL model," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 9(1), pages 62-74.
    7. Yulian Zhang & Shigeyuki Hamori, 2020. "Forecasting Crude Oil Market Crashes Using Machine Learning Technologies," Energies, MDPI, vol. 13(10), pages 1-14, May.
    8. Yanfang Zhang & Mushang Lee, 2019. "A Hybrid Model for Addressing the Relationship between Financial Performance and Sustainable Development," Sustainability, MDPI, vol. 11(10), pages 1-15, May.
    9. S. Thomas Ng & Ryan Fan & James Wong & Albert Chan & Y. H. Chiang & Patrick Lam & Mohan Kumaraswamy, 2009. "Coping with structural change in construction: experiences gained from advanced economies," Construction Management and Economics, Taylor & Francis Journals, vol. 27(2), pages 165-180.
    10. Jiang, Cuiqing & Zhou, Yiru & Chen, Bo, 2023. "Mining semantic features in patent text for financial distress prediction," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    11. Nandita Mishra & Shruti Ashok & Deepak Tandon, 2024. "Predicting Financial Distress in the Indian Banking Sector: A Comparative Study Between the Logistic Regression, LDA and ANN Models," Global Business Review, International Management Institute, vol. 25(6), pages 1540-1558, December.
    12. Zhao Wang & Cuiqing Jiang & Huimin Zhao, 2022. "Know Where to Invest: Platform Risk Evaluation in Online Lending," Information Systems Research, INFORMS, vol. 33(3), pages 765-783, September.
    13. Jiang, Cuiqing & Lyu, Ximei & Yuan, Yufei & Wang, Zhao & Ding, Yong, 2022. "Mining semantic features in current reports for financial distress prediction: Empirical evidence from unlisted public firms in China," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1086-1099.
    14. Guanping Zhou, 2019. "Financial distress prevention in China: Does gender of board of directors matter?," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 9(6), pages 1-8.
    15. Chan Swee Lean, 2001. "Empirical tests to discern linkages between construction and other economic sectors in Singapore," Construction Management and Economics, Taylor & Francis Journals, vol. 19(4), pages 355-363.
    16. ElBannan, Mona A., 2021. "On the prediction of financial distress in emerging markets: What matters more? Empirical evidence from Arab spring countries," Emerging Markets Review, Elsevier, vol. 47(C).
    17. Yong Sun & Hui Liu & Jiwei Liu & Mingyu Sun & Qun Li, 2023. "Analysis of Factors Influencing the Corporate Performance of Listed Companies in China’s Agriculture and Forestry Sector Based on a Panel Threshold Model," Sustainability, MDPI, vol. 15(2), pages 1-21, January.
    18. Ihsan Issa Ahmad Hosani & Fikri T. Dweiri & Udechukwu Ojiako, 0. "A study of cost overruns in complex multi-stakeholder road projects in the United Arab Emirates," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 0, pages 1-10.
    19. Ozili, Peterson K, 2023. "The acceptable R-square in empirical modelling for social science research," MPRA Paper 115769, University Library of Munich, Germany.
    20. Muhammad Irfan & Sanam Zaib Khan & Nasruddin Hassan & Mazlan Hassan & Muhammad Habib & Salma Khan & Hadi Hassan Khan, 2021. "Role of Project Planning and Project Manager Competencies on Public Sector Project Success," Sustainability, MDPI, vol. 13(3), pages 1-19, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vrs:otamic:v:15:y:2023:i:1:p:192-212:n:14. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.