Konut Projelerinde İdeal İş Süresinin Tahmini İçin Bir Hesaplama Yöntemi Önerisi

Yıl 2023, Cilt: 16 Sayı: 4, 2309 - 2336, 16.12.2023

Hakan Tıratacı , Hakan Yaman

https://doi.org/10.35674/kent.1281689

Öz

İnşaat projelerinde süresel gecikmelerin yönetimi, dünya genelinde araştırmacılar arasında büyük ilgi görmektedir. Bu konudaki geniş literatür, iş süresini etkileyen çok sayıda faktör olduğunu öne sürmektedir. Bu faktörlerle iş süresini belirmeye yönelik tahmin yöntemleri, daha güvenilir araçlar ve etkin zaman performansı sağlamak açısından önceki araştırmalarda kullanılmıştır. İş süresi hesaplama tekniklerinin önemli potansiyeli olmasına rağmen, bu yöntemler sınırlı sayıdaki çalışmada ihale aşamasında ve konut projelerinde uygulanmıştır. Ayrıca Türkiye’de inşaat süresi ile ilgili araştırmalar, konut projelerinde önemli gecikmeler olduğunu göstermiştir. Bu nedenle “İdeal İş Süresi”ne ulaşmak amacıyla yeni bir hesaplama yöntemi önermek için sadece konut projelerinde inşaat süresini etkileyen faktörlerin araştırılmasına karar verilmiştir. Konut projelerine ilişkin veriler, Türkiye'de konut projeleri inşa etmede temel kurum olan Türkiye Cumhuriyeti Toplu Konut İdaresi Başkanlığı'ndan (TOKİ) elde edilmiştir. İstatistiksel veri analizinde çoklu regresyon, CHAID ve CART analizleri kullanılmıştır. Çalışmanın bulguları, her bir istatistiksel yöntem için İdeal İş Süresini önemli ölçüde etkileyen birkaç faktörün olduğunu göstermiştir. Her üç istatistiksel yöntemin de geçerliliğini test etmek için kestirim değerleri ve standart hatalar hesaplanmıştır. Regresyon formülü, önerilen hesaplama yönteminin sınanmasında istatistiksel anlamlılık göstermiştir. Yöntemin farklı konut projelerine de uygulanması, geciken proje sayısının önemli ölçüde azaldığını kanıtlamıştır.

Anahtar Kelimeler

Proje Yönetimi, İdeal İş Süresi, Süre Planlaması, Proje Gecikmeleri, CHAID, CART

A Calculation Method Proposal For Estimation of Ideal Construction Duration in Housing Projects

Öz

The management of delays in construction projects is of great interest among researchers around the world. The extensive literature on this topic suggests that there are many factors affecting construction duration. Estimation methods for determining construction duration with these factors have been used in previous studies to provide more reliable tools and effective time performance. Although construction duration calculation techniques have significant potential, these methods have been applied in a limited number of studies regarding tender stage and housing projects. In addition, research on construction duration in Turkey have shown that there are significant delays in housing projects. Therefore, in order to propose a novel calculation method to reach the “Ideal Construction Duration”, it was decided to investigate the factors affecting the construction duration only in housing projects. Data on housing projects were obtained from the Housing Development Administration of Turkey (TOKI), which is the main institution in constructing housing projects. Multiple regression, CHAID and CART methods were used in statistical data analysis. The findings of the study showed that there are several factors that significantly affect the Ideal Construction Duration for each statistical method. To test the validity of all three statistical methods, cutoff values and standard errors were calculated. The regression formula showed statistical significance in testing the proposed calculation method. The implementation of proposed method to different housing projects has proven that the number of delayed projects has significantly decreased.

Anahtar Kelimeler

Project Management, Ideal Construction Duration, Scheduling, Project Delays, CHAID, CART

Kaynakça

• Abd El-Razek, M. E., Bassioni, H. A., & Mobarak, A. M. (2008). Causes of delay in building construction projects in Egypt. Journal of Construction Engineering and Management, 134(11), 831–841. https://doi.org/10.1061/(ASCE)0733-9364(2008)134:11(831)
• Adul-Hamid, R. (1996). Construction duration prediction using neural network methodology (PhD Thesis). University of Manchester.
• Ahuja, H. N., & Nandakumar, V. (1985). Simulation model to forecast project completion time. Journal of Construction Engineering and Management, 111(4), 325–342. https://doi.org/10.1061/(ASCE)0733-9364(1985)111:4(325)
• Aibinu, A. A., & Jagboro, G. O. (2002). The effects of construction delays on project delivery in Nigerian construction industry. International Journal of Project Management, 20(8), 593-599. https://doi.org/10.1016/S0263-7863(02)00028-5
• Aibinu, A. A., & Odeyinka, H. A. (2006). Construction delays and their causative factor in Nigeria. Journal of Construction Engineering and Management ASCE,132(7), 667-677. https://doi.org/10.1061/(ASCE)0733-9364(2006)132:7(667)
• Aksoy, B., & Boztosun, D. (2021). Comparison of classification performance of machine learning methods in prediction financial failure: Evidence from Borsa İstanbul. Hitit Journal of Social Science, 14(1), 56-86. doi: 10.17218/hititsbd.880658
• Alaghbari, W., Kadir, M.R.A., Salim, A., & Ernawati. (2005). Significant factors causing delay of building construction projects in Malaysia. Engineering, Construction and Architectural Management, 14(2), 192–206. https://doi.org/10.1108/09699980710731308
• Alfalasi, A.A. (2016). Developing a framework for improving business continuity management success (BCM) in UAE construction ındustry (MSc Thesis). The British University in Dubai.
• Aliverdi, R., Naeni, L. M., & Salehipour, A. (2013). Monitoring project duration and cost in a construction project by applying statistical quality control charts. International Journal of Project Management, 31(3), 411–423. https://doi.org/10.1016/j.ijproman.2012.08.005
• Al-Khalil, M. I., & Al-Ghafly, M. A. (1999). Important causes of delay in public utility projects in Saudi Arabia.Construction Management & Economics, 17(5), 647-655.
• Al-Sabah, R., Menassa, C. C., & Hanna, A. (2014). Evaluating impact of construction risks in the Arabian Gulf Region from perspective of multinational architecture, engineering and construction firms. Construction Management and Economics, 32(4), 382-402. https://doi.org/10.1080/01446193.2014.884281
• Alshihri, S., Al-Gahtani, K., & Almohsen, A. (2022). Risk factors that lead to time and cost overruns of building projects in Saudi Arabia. Buildings, 12(7), 902. https://doi.org/10.3390/buildings12070902
• Arditi, D., Akan, G. T., & Gurdamar, S. (1985). Reasons for delays in public projects in Turkey. Construction Management and Economics, 3, 171-181. https://doi.org/10.1080/01446198500000013
• Asnaashari, E., Knight, A., Hurst, A., & Farahani, S. S. (2009). Causes of construction delays in Iran: project management, logistics, technology and environment. ARJ Dainty, (Ed.), Proceedings 25th Annual ARCOM Conference, Nottingham, UK.
• Assaf, S.A., & Al-Hejji, S. (2006). Causes of delay in large construction projects. International Journal of Project Management, 24, 349-357. https://doi.org/10.1016/j.ijproman.2005.11.010
• Baltacı, M.K. (2012). TOKİ’nin arsa satışı karşılığı gelir paylaşımı modeli üzerine bir inceleme (Yayınlanmamış yüksek lisans tezi). Yıldız Teknik Üniversitesi.
• Baqerin, M. H., Shafahi, Y., & Kashani, H. (2016). Application of Weibull Analysis to Evaluate and Forecast Schedule Performance in Repetitive Projects. Journal of Construction Engineering and Management, 142(2), 04015058. doi:10.1061/(asce)co.1943-7862.0001040
• Bin Seddeeq, A., Assaf, S., Abdallah, A., & Hassanain, M. A. (2019). Time and cost overrun in the Saudi Arabian oil and gas construction industry. Buildings, 9(2), 41. https://doi.org/10.3390/buildings9020041
• Birgönül, M.T., Dikmen, İ., Ozorhon, B., & Işık, Z. (2007, 30-31 Ekim). İnşaat sektörünün yapım yönetimi eğitiminden beklentileri [Konferans sunumu]. 4. Inşaat Yönetimi Kongresi, ODTÜ, Ankara.
• Blyth, K., Lewis, J., & Kaka, A. (2004). Predicting project and activity duration for buildings in the UK. Journal of Construction Research, 5(2), 329-347. https://doi.org/10.1142/S1609945104000097
• Cevahir, E. (2020). SPSS ile nicel veri analizi rehberi (1. Baskı). Kibele Yayınları.
• Chan, A.P.C., & Chan, A.P.L. (2004). Key performance indicators for measuring construction success. Benchmarking: An International Journal, 11(2), 203-221.
• Chan, D.M.W., & Kumaraswamy, M.M. (1997). A comparative study of causes of time overruns in Hong Kong construction projects. International Journal of Project Management, 15(1), 55-63.
• Chan, D.M.W., & Kumaraswamy, M.M. (2002). Compressing construction durations: lessons learned from Hong Kong building projects. International Journal of Project Management, 20(1), 23-35. https://doi.org/10.1016/S0263-7863(00)00032-6
• Chao, L-C., & Chien, C-F. (2010). A model for updating project s-curve by using neural networks and matching progress. Automation in Construction, 19(1), 84-91. https://doi.org/10.1016/j.autcon.2009.09.006
• Cheng, Y.-M. (2014). An exploration into cost-influencing factors on construction projects. International Journal of Project Management, 32(5), 850-860. https://doi.org/10.1016/j.ijproman.2013.10.003
• Chevallier, N., & Russell, A. (2001). Developing a draft schedule using templates and rule. Journal of Construction Engineering & Management, 127(5), 391-398.
• Chong, C.T. (2006). Determination of civil engineering construction time duration (Final Year Project Report). University of Malaysia Sarawak.
• Chipman, H.A. George, E.I., & McCulloch, R.E. (2000). Hierarchical priors for bayesian CART shrinkage. Statistic and Computing, 10(1), 17-24. https://doi.org/10.1023/A:1008980332240
• Cumhurbaşkanlığı Strateji ve Bütçe Başkanlığı. (2019). On birinci kalkınma planı (2019-2023). Ankara.
• Doloi, H., Sawhney, A., & Iyer, K. C. (2012). Structural equation model for investigating factors affecting delay in Indian construction projects. Construction Management and Economics, 30(10), 869-884. https://doi.org/10.1080/01446193.2012.717705
• DPT (2001). Sekizinci kalkınma planı (2001-2006). Ankara.
• DPT (2007). Dokuzuncu kalkınma planı (2007-2013). Ankara.
• Dursun, O., & Stoy, C. (2012). Determinants of construction duration for building projects in Germany. Engineering, Construction and Architectural Management, 19(4), 444–468. doi:10.1108/09699981211237139
• Elinwa, A. U., & Joshua, M. (2001). Time-overrun factors in Nigerian construction industry. Journal of Construction Engineering and Management, 127(5), 419-425.
• Endut, I. R., Akintoye, A., & Kelly, J. (2009). Cost and time overruns of projects in Malaysia. Glasgow Caledonian University. https://www.irbnet.de/daten/iconda/CIB10633.pdf
• Erbaş, İ., & Çıracı, A. M. (2013). Construction project delivery system as a form of project implementation in Turkish Public Procurement. E-Journal of New World Sciences Academy, 8, 108-119.
• Fan, S-L., Yeh, I-C., & Chi, W-S. (2021). Improvement in estimating durations for building projects using artificial neural network and sensitivity analysis. Journal of Construction Engineering Management, 147(7), 04021050. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002036
• Faremi, O., Ogunsanmi, O., & Kohn, I. (2016). Factors affecting cost and time control in construction projects. Lagos Journal of Environmental Studies, 8(1), 94-102. https://ir.unilag.edu.ng/handle/123456789/8373
• FIDIC. (2017). Conditions of contract for construction (2nd Ed.). Fédération Internationale des Ingénieurs-Conseils.
• Field, A. (2009). Discovering statistics using SPSS (3rd Ed.). Sage Publications.
• Fu, C.Y. (2004). Combining loglinear model with classification and regression tree (CART): an application to birth data. Computational Statistics & Data Analysis, 45(4), 865-874.
• Geng, R., Bose, I., &Chen, X. (2015). Prediction of financial distress: an empirical study of listed Chinese companies using data mining. European Journal of Operational Research, 241, 236-247. doi: 10.1016/j.ejor.2014.08.016
• Gibson Jr, G. E., Wang, Y.R., Cho, C. S., & Pappas, M.P. (2006). What is preproject planning, anyway? Journal of Management in Engineering, 22(1), 35–42.
• Girth, A. M., & Lopez, L. E. (2019). Contract design, complexity, and incentives: Evidence from US federal agencies. The American Review of Public Administration, 49(3), 325–337. https://doi.org/10.1177/0275074018787558
• Godinho, P.C., & Costa, J.P. (2004). The use of cost and time in project decision trees: a model and an application. Notas Económicas, 1-22.
• Haas, O., Huschbeck, T., & Markovič, P. (2022). Effects of Theft on the critical path of construction projects. N. Kryvinska & M. Greguš (Eds.), Developments in information & knowledge management for business applications (pp. 59-78). Springer.
• Hagquist, C., & Stenbeck, M. (1998). Goodness of fit in regression analysis-R2 and G2 reconsidered. Quality & Quantity, 32, 229-245. https://doi.org/10.1023/A:1004328601205
• Hoffman, G. J., Thal, A. E., Webb, T. S., & Weir, J. D. (2007). Estimating performance time for construction projects. Journal of Management in Engineering, 23(4), 193-199.
• Hosseinian, S.M., & Reinschmidt, K.F. (2015). Finding best model to forecast construction duration of road tunnels with new Austrian tunneling method using Bayesian inference: Case study of Niayesh highway tunnel in Iran. Transportation Research Record: Journal of the Transportation Research Board, 2522(1), 113–120. https://doi.org/10.3141/2522-11
• Hwang, B.G., Zhao, X., & Ng, S.Y. (2013). Identifying the critical factors affecting schedule performance of public housing projects. Habitat International, 38, 214–221. https://doi.org/10.1016/j.habitatint.2012.06.008
• Ibironke, O.T., & Elamah, D. (2011). Factors affecting time, cost and quality management in building construction projects. FUTY Journal of the Environment, 6(1), 1-9.
• Imbert, D.I. (1990). Human issues affecting construction in developing countries. Construction Management and Economics, 8(2), 219-228.
• Ismail, S. (2013). Factors attracting the use of public private partnership in Malaysia. Journal of Construction in Developing Countries, 18(1), 95-108.
• Iyer, K. C., Chaphalkar, N. B., & Joshi, G. A. (2008). Understanding time delay disputes in construction contracts. International Journal of Project Management, 26(2), 174–184.
• Iyer, K.C., & Jha, K.N. (2005) Factors affecting cost performance: evidence from Indian construction projects. International Journal of Project Management, 23, 28-295. https://doi.org/10.1016/j.ijproman.2007.05.002
• Jin, R.Z., Han, S.W., Hyun, C.T., & Cha, Y.W. (2016). Application of case-based reasoning for estimating preliminary duration of building project. Journal of Management in Engineering, 142(2), 04015082-1-8. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001072
• Kaka, A., & Price, A.D.F. (1991). Relationship between value and duration of construction projects. Construction Management & Economics, 9(4), 383-400.
• Kaliba, C., Muya, M., & Mumba, K. (2009). Cost escalation and schedule delays in road construction projects in Zambia. International Journal of Project Management, 27(5), 522–531. https://doi.org/10.1016/j.ijproman.2008.07.003
• Kaming, P. F., Olomolaiye, P. O., Holt, G. D., & Harris, F. C. (1997). Factors influencing construction time and cost overruns on high-rise projects in Indonesia. Construction Management & Economics, 15(1), 83-94.
• Kaplan, S. (2012). İdeal bir kamu ihale kanunu ve ideal bir kamu ihale kurumu ve kurulu nasıl olmalıdır? Fonksiyonel bir model çalışması. Maliye Dergisi, 162, 18-50.
• Karapınar, O. (2005). 2886 ve 4734 sayılı ihale kanunlarının incelenmesi ve yapım işlerinde 4734 sayılı kamu ihale kanunun uygulanmasında karşılaşılan sorunlar için çözüm önerileri (Yayınlanmamış yüksek lisans tezi). İstanbul Teknik Üniversitesi.
• Kerzner, H. (1992). Project management: a systems approach to planning, scheduling, and controlling (4th Ed.). Van Norstrand Reinhold Co.
• Khosrowshahi, F., & Kaka, A. P. (1996). Estimation of project total cost and duration for housing projects in the U.K. Building and Environment, 31(4), 375-383.
• Koc, S., & Ulucan, S. (2016). Testing of Altman Z methods which is used for detecting of financial failures with fuzzy logic (Anfis) technique: a case study on technology and textile sector. Journal of Finance Letters, 106, 147-167. doi: 10.33203/mfy.341768
• Koushki, P. A., Al‐Rashid, K., & Kartam, N. (2005). Delays and cost increases in the construction of private residential projects in Kuwait. Construction Management and Economics, 23(3), 285–294. https://doi.org/10.1080/0144619042000326710
• Köktaş, A., Karaosmanoğlu, F., & Bilgiç, F.K. (2009). Kamu ihaleleri ve etik. Yolsuzluğun önlenmesi için etik projesi. Akademik Araştırma Çalışması.
• Kumar, S.S. & Cheng, J.C.P. (2015). A BIM-based automated site layout planning framework for congested construction sites. Automation in Construction, 59, 24–37. https://doi.org/10.1016/j.autcon.2015.07.008
• Le-Hoai, L., Lee, Y. D., & Lee, J. Y. (2008). Delay and cost overruns in Vietnam large construction projects: A comparison with other selected countries. KSCE Journal of Civil Engineering, 12(6), 367–377. https://doi.org/10.1007/s12205-008-0367-7
• Lessing, B., Thurnell, D., & Durdyev, S. (2017). Main factors causing delays in large construction projects: Evidence from New Zealand. Journal of Management, Economics and Industrial Organization, 1(2), 63–82. doi:10.31039/jomeino.2017.1.2.5
• Lewis-Beck, M.S. (1980). Applied regression: An introduction. Sage Publications.
• Li, H., Chen, Z., Yong, L., & Kong, S.C.W. (2005). Application of integrated GPS and GIS technology for reducing construction waste and improving construction efficiency. Automation in Construction, 14(3), 323–331. https://doi.org/10.1016/j.autcon.2004.08.007
• Lin, C-L., & Fan, C-L. (2019). Evaluation of CART, CHAID, and QUEST algorithms: a case study of construction defects in Taiwan. Journal of Asian Architecture and Building Engineering, 18(6), 539-553. https://doi.org/10.1080/13467581.2019.1696203
• Lin, M.-C., Tserng, H. P., Ho, S.-P., & Young, D.-L. (2011), Developing a construction-duration model based on a historical dataset for building project. Journal of Civil Engineering and Management, 17(4), 529-539. https://doi.org/10.3846/13923730.2011.625641
• Lines, B.C., Sullivan, K.T., Smithwick, J.B., & Mischung, J. (2015). Overcoming resistance to change in engineering and construction: Change management factors for owner organizations. International Journal of Project Management, 33(5), 1170-1179. https://doi.org/10.1016/j.ijproman.2015.01.008
• Lines, B.N., Sullivan, K.T., Hurtado, K.C., & Savicky, J. (2014). Planning in construction: longitudinal study of pre-contract planning model demonstrates reduction in project cost and schedule growth.International Journal of Construction Education and Research, 11(1), 21–39. https://doi.org/10.1080/15578771.2013.872733
• Lo, T. Y., Fung, I. W. H., & Tung, K. C. F. (2006). Construction delays in Hong Kong civilengineering projects. Journal of Construction Engineering and Management, 132(6), 636–649. https://doi.org/10.1061/(ASCE)0733-9364(2006)132:6(636)
• Luu, V., Kim, S., Van Tuan, N., & Ogunlana, S. (2009). Quantifying schedule risk in construction projects using Bayesian belief networks. International Journal of Project Management, 27(1), 39-50. https://doi.org/10.1016/j.ijproman.2008.03.003
• Mahmoodzadeh, A., Nejati, H.R., & Mohammadi, M. (2022). Optimized machine learning modelling for predicting the construction cost and duration of tunneling projects. Automation in Construction, 139, 104305. https://doi.org/10.1016/j.autcon.2022.104305
• Majid, I.A. (2006). Causes and effect of delays in Aceh construction industry (Unpublished master’s thesis). University of Technology Malaysia.
• Mauriya, V. K., Yadav, P. K., & Angra, V. K. (2010, 16-18 December). Challenges and strategies for tunnelling in the Himalayan Region. Indian Geotechnical Conference’ 2010,GEO Trendz, India.
• McCord, J., McCord, M., Davis, P. T., Haran, M., & Rodgers, W.J. (2015). Understanding delays in housing construction: Evidence from Northern Ireland. Journal of Financial Management of Property and Construction, 20(3), 286-319. doi:10.1108/jfmpc-07-2015-0028
• Meeampol, S., & Ogunlan, S.O. (2006). Factors affecting cost and time performance on highway construction projects: Evidence from Thailand. Journal of Financial Management of Property and Construction, 11(1), 3-20. https://doi.org/10.1108/13664380680001076
• Memon, A. H., Rahman, I. A., & Azis, A. A. A. (2012). Time and cost performance in construction projects in southern and central regions of Peninsular Malaysia. International Journal of Advances in Applied Sciences, 1(1), 45–52. http://doi.org/10.11591/ijaas.v1.i1.pp45-52
• Memon, A.H. (2014). Contractor perspective on time overrun factors in Malaysian construction projects. International Journal of Science, Environment and Technology, 3(3), 1184-1192.
• Mooi, E., & Sarstedt, M. (2011). A concise guide to market research: The Process, data, and methods using IBM SPSS statistics. Springer Verlag.
• Musarat, M. A., Alaloul, W. S., & Liew, M. S. (2021). Impact of inflation rate on construction projects budget: A review. Ain Shams Engineering Journal, 12(1), 407–414. https://doi.org/10.1016/j.asej.2020.04.009
• Nani, G., Mensah, I., & Adjei-Kumi, T. (2017). Duration estimation model for bridge construction projects in Ghana. Journal of Engineering, Design and Technology, 15(6), 754-777. doi:10.1108/JEDT-04-2017-0029
• Nasirzadeh, F., & Nojedehi, P. (2013). Dynamic modeling of labor productivity in construction projects. International Journal of Project Management, 31(6), 903-911. https://doi.org/10.1016/j.ijproman.2012.11.003
• Nayak, V.K.(2019). Study on factors affecting time overrun in rural infrastructure projects (case study: mission Kakatiya) [Vinod Paper Representation]. https://www.academia.edu/40915067/STUDY_ON_FACTORS_AFFECTING_TIME_OVERRUN_IN_RURAL_INFRASTRUCTURE_PROJECTS_Case_Study_MISSION_KAKATIYA
• Ndekugri, I., Braimah, N., & Gameson, R. (2008). Delay analysis within construction contracting organizations. Journal of Construction Engineering and Management, 134(9), 692-700. https://doi.org/10.1061/(ASCE)0733-9364(2008)134:9(692)
• Nguyen, L.D., Phan, D.H., & Tang, L.C.M. (2013). Simulating construction duration for multistory buildings with controlling activities. Journal of Construction Engineering and Management, 139(8), 951-959. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000677
• Noorzai, E., Gharouni Jafari, K., & Moslemi Naeni, L. (2022). Lessons Learned on selecting the best mass housing method based on performance evaluation criteria in Iran. International Journal of Construction Education and Research, 18(2), 1-19. doi:10.1080/15578771.2020.1867258
• O’Brien, J.J., & Plotnick, F.L. (1999). CPM in construction management. McGraw-Hill.
• Obodo, C. E., Xie, Z. N., Cobbinah, B. B., & Yari, K. D. Y. (2021). Evaluating the factors affecting contractors tender for project construction: An Empirical study of small-scale indigenous contractors in Awka, Nigeria.Open Journal of Social Sciences, 9, 381-397. doi:10.4236/jss.2021.97028
• Odabaşı, E. (2009). Models for estimating construction duration: An application for selected buildings on the METU campus (Yayınlanmamış yüksek lisans tezi). Orta Doğu Teknik Üniversitesi.
• Odeh, A. M., & Battaineh, H. T. (2002). Causes of construction delay: traditional contracts. International Journal of Project Management, 20(1), 67-73. https://doi.org/10.1016/S0263-7863(00)00037-5
• Oleinik, P., Cherednichenko, N., Shvedov, S., & Melnichuk, V. (2019, 10-12 December). The principles of justification of an object construction duration. E3S Web of Conferences, 110, 02126. https://doi.org/10.1051/e3sconf/201911002126
• Oo, B.L., Lim, T.H.B., & Runeson, G. (2022), Critical factors affecting contractors’ decision to bid: a global perspective. Buildings, 12, 379. https://doi.org/10.3390/buildings12030379
• Oyedele, L. O, Jaiyeoba, B. E., Kadiri, K. O, Folagbade, S. O., Tijani I. K., & Salami R. O. (2015). Critical factors affecting construction quality in Nigeria: evidence from industry professionals. International Journal of Sustainable Building Technology and Urban Development, 6(2), 103-113. https://doi.org/10.1080/2093761X.2015.1033662
• Oyedele, L.O. (2013). Avoiding performance failure payment deduction in PFI/PPP projects: model of critical success factors. Journal of Performance of Constructed Facilities, 27, 283-294. https://doi.org/10.1061/%28ASCE%29CF.1943-5509.0000367
• Oyedele, O.A. (2017). A study into the factors affecting duration of construction projects in Nigeria. Femi Oyedele & Co. https://www.researchgate.net/publication/313842757_A_study_into_the_factors_affecting_duration_of_construction_projects_in_Nigeria
• Oyewobi, L. O., & Ogunsemi, D. R. (2010). Factors influencing reworks occurrence in construction: A study of selected building projects in Nigeria. Journal of Building Performance, 1(1), 1–20.
• Ozdamar, K. (2004). Paket programlar ile istatistiksel veri analizi 2. Kaan Kitapevi.
• Papatheocharous, E., & Andreou, A.S. (2012). A Hybrid software cost estimation approach utilizing decision trees and fuzzy logic. International Journal of Software Engineering and Knowledge Engineering, 22(3), 435-465. https://doi.org/10.1142/S0218194012500106
• Park, H. S., Lee, D., Kim, S., & Kim, J.L. (2015). Comparing project performance of design-build and design-bid-build methods for large-sized public apartment housing projects in Korea. Journal of Asian Architecture and Building Engineering, 14(2), 323-330.
• Polat, G., & Bingol, B.N. (2017). Data envelopment analysis (DEA) approach for making the bid/no bid decision: A case study in a Turkish construction contracting company. Scientia Iranica, 24(2), 497-511.
• Polat, G., Kaplan, B., & Bingöl, B.N. (2015). Subcontractor selection using genetic algorithm. Procedia Engineering, 123, 432–440. https://doi.org/10.1016/j.proeng.2015.10.081
• Pospieszny, P. (2015). Application of data mining techniques for effort and duration estimation of software projects (PhD Thesis). Warsaw School of Economics.
• Qiao, Y., Labi, S., & Fricker, J.D. (2019). Hazard-based duration models for predicting actual duration of highway projects using nonparametric and parametric survival analysis. Journal of Management in Engineering, 35(6), 04019024. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000700
• Ramli, N.A., Abdullah, C.S., Mohd Nawi, M.N., Zalazilah, M.H., Othuman Mydin, M.A., & Hamid, Z.A. (2018). A model of load-bearing masonry (LBM) technology adoption: Empirical study in the Malaysia Country. Malaysian Construction Reserarch Journal, 3(1), 204-217.
• Rudeli, N., Santilli, A., Puente, I., & Viles, E. (2017). Statistical Model for Schedule Prediction: Validation in a Housing-Cooperative Construction Database. Journal of Construction Engineering and Management, 143(11), 04017083. doi:10.1061/(asce)co.1943-7862.0001396
• Salleh, R. (2009). Critical success factors of project management for Brunei construction projects: improving project performance (Doctoral dissertation). Queensland University of Technology.
• Sanni-Anibire, M.O., Zin, R.M., & Olatunji, S.O. (2021). Developing a machine learning model to predict the construction duration of tall building projects. Journal of Construction Engineering, Management & Innovation, 4(1), 22-36.
• Shanmugapriya, S., & Subramanian, K. (2013). Investigation of significant factors influencing time and cost overruns in Indian construction projects. International Journal of Emerging Technology and Advanced Engineering, 3(10), 734-740.
• Shokri-Ghasabeh, M., & Chileshe, N. (2016). Critical factors influencing the bid/no bid decision in the Australian construction industry. Construction Innovation, 16, 127-157. https://doi.org/10.1108/CI-04-2015-0021
• Smugala, S., & Kubečková, D. (2021, June 14-18). Construction process duration predicted by statistical method[Conference paper]. IOP Conference Series: Materials Science and Engineering, Prague, Czech Republic. https://doi.org/10.1088/1757-899X/1203/3/032135
• Soong, T. (2004). Fundamentals of probability and statistics for engineers. Wiley.
• Sönmez, M. (2019). Türkiye’de üstyapı projelerinde zaman-maliyet ilişkileri (Doktora tezi). Sakarya Üniversitesi.
• Susanti, R. (2020). Cost overrun and time delay of construction project in Indonesia. Journal of Physics: Conference Series, 1444(1), 012050. https://doi.org/10.1088/1742-6596/1444/1/012050
• Sweis, J.G. (2013). Factors affecting time overruns in public construction projects: the case of Jordan. International Journal of Business and Management, 8(23), 120-129. doi:10.5539/ijbm.v8n23p120
• Ting, S.N., Darrell, V.C., Kueh, A.B.H., Lee, Y.Y., & Ng, C.K. (2021, October 27-28). Extension of time (EoT) considerations in construction duration estimate for public construction projects [Conference paper]. IOP Conference Series: Materials Science and Engineering. https://doi.org/10.1088/1757-899X/1101/1/012030
• Tokalakoğlu, D. (2010). Kamu inşaat sektöründe yaklaşık maliyet hesabı şartnamesi oluşturulmasına yönelik bir çalışma (Yayınlanmamış yüksek lisans tezi). İstanbul Teknik Üniversitesi.
• Tunç, G., & Özsaraç, E. (2015, 14-16 Ekim). Türkiye’deki kamu özel işbirliği modelinin iyileştirilmesine ait öneriler [Konferans sunumu]. 3. Türkiye Deprem Mühendisliği ve Sismoloji Konferansı, Dokuz Eylül Üniversitesi.
• Tunji-Olayeni, P.F., Afolabi A.O., & Okpalamoka, O.I. (2018). Survey data set on occupational hazards on construction sites. Data in Brief, 18, 1365-1371. https://doi.org/10.1016/j.dib.2018.04.028
• Türesoy, M. (1989). Yapı üretiminde süre tahmini ve yapım süresini etkileyen faktörler (Yayınlanmamış yüksek lisans tezi). İstanbul Teknik Üniversitesi.
• Ubani, E. C., Okorocha, K. A., & Emeribe, S. C. (2013). Analysis of factors influencing time and cost overruns on construction projects in Southeastern Nigeria. International Journal of Management Sciences and Business Research, 2(2), 73-84.
• Ujong, J., Mbadike, E. M., & Alaneme, G. U. (2022). Prediction of cost and duration of building construction using artificial neural network. Asian Journal of Civil Engineering, 23, 1117-1139. doi:10.1007/s42107-022-00474-4
• Usta, Y. (2014). Kamusal kalkınmada proje yönetimine yönelik modelsel bir yaklaşım. Verimlilik Dergisi, 3, 115-139.
• Walker, D. H. T., & Vines, M. W. (2000). Australian multi-unit residential Projectconstruction time performance factors. Engineering, Construction and Architectural Management, 7(3), 278–284.
• Walraven, A., & de Vries, B. (2009). From demand driven contractor selection towards value driven contractor selection. Construction Management and Economics, 27, 597-604. https://doi.org/10.1108/eb021152
• Wang, Y. R., Yu, C. Y., & Chan, H. H. (2012). Predicting construction cost and schedule success using artificial neural networks ensemble and support vector machines classification models. International Journal of Project Management, 30(4), 470-478. https://doi.org/10.1016/j.ijproman.2011.09.002
• Williams, R. C. (2008). The development of mathematical models for preliminary prediction of highway construction duration (Doctoral dissertation). Virginia Tech.
• Woolery, J. C., & Crandall, K. C. (1983). Stochastic network model for planning scheduling. Journal of Construction Engineering and Management, 109(3), 342–354.
• Yang, R. J., Wang, Y., & Jin, X.-H. (2014). Stakeholders’ attributes, behaviors, and decision-making strategies in construction projects: importance and correlations in practice. Project Management Journal, 45(3), 74-90.
• Yargıtay. (2010). 2010/2081 Esas ve 2010/9729 Sayılı Karar. Yargıtay Hukuk Genel Kurulu Kararları.
• Yargıtay. (2011). 2011/4202 Esas ve 2011/14042 Sayılı Kararı. Yargıtay Hukuk Genel Kurulu Kararları.
• Yargıtay. (2013). 2012/24284 Esas ve 201/1694 Sayılı Kararı. Yargıtay Hukuk Genel Kurulu Kararları.
• Yargıtay. (2014). 2013/13 – 1143 Esas ve 2014/625 Sayılı Kararı. Yargıtay Hukuk Genel Kurulu Kararları.
• Yargıtay. (2015). 2013/13 – 2342 Esas ve 2015/1066 Sayılı Kararı. Yargıtay Hukuk Genel Kurulu Kararları.
• Yaseen, Z.M., Ali, Z.H., Salih, S.Q., & Al-Ansari, N. (2020). Prediction of risk delay in construction projects using a hybrid artificial intelligence model. Sustainability, 12, 1514.
• Yeom, D-J., Seo, H-M., Kim, Y-J., Cho, C-S., & Kim, Y. (2018). Development of an approximate construction duration prediction model during the project planning phase for general office buildings. Journal of Civil Engineering and Management, 24(3), 238-253. https://doi.org/10.3846/jcem.2018.1646
• Yogesh, G., & Hanumanth Rao, C. (2021). A study on linear scheduling methods in road construction projects. Materials Today: Proceedings, 47(4), 5475-5478. https://doi.org/10.1016/j.matpr.2021.07.393