Development of a mathematical model to predict the cost of Ethiopian Roads Authority road projects: the case of Ethiopia

References

• Abera, M. A. B. (2016). Bridge and culvert hydraulics (HENG – 5203) lecture-01 : Introduction. U.S. Department of Transportation Federal Highway Administration.
   Google Scholar
• Adel, K., Elyamany, A., Belal, A. M., & Kotb, A. S. (2016). Developing parametric model for conceptual cost estimate of highway projects. International Journal of Engineering Science, 6(7), 1728–1734.
   Google Scholar
• Akinradewo, O., Aigbavboa, C., Oke, A. E., & Data, B. (2020). Road projects estimation: A review road projects estimation: A review. Proceedings of the International Conference on Industrial Engineering and Operations Management Dubai, UAE, 2108-2113.
   Google Scholar
• Akintoye, A. S. (1999, September 8). Factors influencing the project cost estimating decision [paper presentation]. CIB W55 & W65 Joint Triennial Symposium Customer Satisfaction : A Focus for Research & Practice. United Kingdom.
   Google Scholar
• Alemayehu, S. (2014a). Testing regression models to estimate costs of road construction projects. Jesuit Historical Institute In Africa(Jhia).
   Google Scholar
• Alemayehu, S. (2014b). Testing regression models to estimate cost of road construction projects of science in civil engineering (construction technology and management). Jesuit Historical Institute In Africa(Jhia).
   Google Scholar
• Andom, D. (2015). A thesis submitted to the School of Graduate Studies, Addis Ababa University Institute of Technology in partial fulfillment of the requirements for the degree of evaluation of the cost estimating system of building contractors in Addis Ababa. Institute of Technology.
   Google Scholar
• Attal, A. (2010, August). Development of neural network models for prediction of highway construction cost and project duration. Proceeding of the joint Conference on computing in Construction (JC3).
   Google Scholar
• Befkadu, A., Quezon, P. E. T., & Busier, M. (2016). Assessment on the effects of weather change on road construction planning at some selected projects in Addis Ababa and Oromia. International Journal of Scientific and Engineering Research.
   Google Scholar
• Chakraborty, D., Elzarka, H., & Bhatnagar, R. (2016). Generation of accurate weather files using a hybrid machine learning methodology for design and analysis of sustainable and resilient buildings. Sustainable Cities and Society, 24, 33–41. https://doi.org/10.1016/j.scs.2016.04.009
   Web of Science ®Google Scholar
• De Bock, L. P., & Van den Bergh, H. (2004). Stainless steel slags in hydraulic bound mixtures for road construction, 2 case studies in Belgium. In International RILEM Conference on the Use of Recycled Materials in Building and Structures (pp. 1095–1104). Belgian Road Research Centre (BRRC).
   Google Scholar
• Dharwadkar, N. V, & Arage, S. S. (2018). Prediction and estimation of civil construction cost using linear regression and neural network. International Journal of Intelligent Systems Design and Computing, 2(1), 28–44. https://doi.org/10.1504/IJISDC.2018.092554
   Google Scholar
• Elmousalami, H. H. (2019). Intelligent methodology for project conceptual cost prediction. Heliyon, 5(5), e01625. https://doi.org/10.1016/j.heliyon.2019.e01625
   PubMed Web of Science ®Google Scholar
• Farr, B. C. (2008). Designing qualitative research. Transformation: An International Journal of Holistic Mission Studies, 25(2–3), 165–166. https://doi.org/10.1177/026537880802500310
   Google Scholar
• Ferreira, J. C., & Patino, C. M. (2015). The p value. Jornal Brasileiro de Pneumologia, 41(5), 485. https://doi.org/10.1590/S1806-37132015000000215
   PubMed Web of Science ®Google Scholar
• Gao, U. (2020, March). Cost estimating and assessment guide. U.S Government Accountability Office.
   Google Scholar
• Gidissa, D. (2017). Factors affecting cost and time performance of construction projects in Ethiopia (case of: public building projects in Addis Ababa). St. Mary’s University Institutional Repository.
   Google Scholar
• Gofhamodimo, C. M. (1999). Construction contracts. Procurement methods in Botswana. Sustainable Design and Construction in Africa.
   Google Scholar
• Hu, M., & Skibniewski, M. J. (2021). A review of building construction cost research: Current status, gaps and green buildings. Green Building & Construction Economics, 2, 1–17. https://doi.org/10.37256/gbce.212021768
   Google Scholar
• Irfan, M., Bilal, M., & Anastasopoulos, P. (2011). anticipated project cost, project type, and contract type planning-stage estimation of highway project duration on the basis of anticipated project cost, project type, and contract type. International Journal of Project Management, 29(1), 78–92. https://doi.org/10.1016/j.ijproman.2010.01.001
   Web of Science ®Google Scholar
• Jamous, E. H. A. (2013). Parametric cost estimation of road projects using artificial neural networks. National Library of Canada.
   Google Scholar
• Juszczyk, M. (2020). Development of cost estimation models based on ANN ensembles and the SVM method. Civil and Environmental Engineering Reports, 30(3), 48–67. https://doi.org/10.2478/ceer-2020-0033
   Web of Science ®Google Scholar
• Kaleem, S., Irfan, M., & Gabriel, H. F. (2014). Estimation of highway project duration at the planning stage and analysis of risk factors leading to time overrun. Second Transportation & Development Congress. https://doi.org/10.1061/9780784413586.059
   Google Scholar
• Kanchana, S., & Janani, S. (2018). A study on factors affecting estimation of construction project. International Research Journal of Engineering and Technology (IRJET), 05(11), 1154–1157.
   Google Scholar
• Kim, D. Y., Kim, B., & Han, S. H. (2008). Two-staged early cost estimation for highway construction projects. In ISARC 2008 - Proceedings from the 25th International Symposium on Automation and Robotics in Construction (pp. 490–495). Institute of Internet and Intelligent Technologies. https://doi.org/10.3846/isarc.20080626.490
   Google Scholar
• Kumari, K., & Yadav, S. (2018). Linear regression analysis study. Journal of the Practice of Cardiovascular Sciences, 4(1), 33. https://doi.org/10.4103/jpcs.jpcs_8_18
   Google Scholar
• Leung, M., Shan, Y., Chan, I., & Dongyu, C. (2011). Engineering, construction and architectural management article information. Engineering, Construction and Architectural Management, 18(3), 312–328. https://doi.org/10.1108/09699981111126205
   Google Scholar
• Liu, M., Le, Y., Hu, Y., Xia, B., Skitmore, M., & Gao, X. (2019). System dynamics modeling for construction management research: Critical review and future trends. Journal of Civil Engineering and Management, 25(8), 730–741. https://doi.org/10.3846/jcem.2019.10518
   Web of Science ®Google Scholar
• Lowe, D. J., Emsley, M. W., & Harding, A. (2006). Predicting construction cost using multiple regression techniques. Journal of Construction Engineering and Management, 132(7), 750–758. https://doi.org/10.1061/(asce)0733-9364(2006)132:7(750)
   Web of Science ®Google Scholar
• Luong, D. L., Tran, D. H., & Nguyen, P. T. (2021). Optimizing multi-mode time-cost-quality trade-off of construction project using opposition multiple objective difference evolution. International Journal of Construction Management, 21(3), 271–283. https://doi.org/10.1080/15623599.2018.1526630
   Web of Science ®Google Scholar
• Mahde Abd, A., Adnan Jasim, N., & Saleh Naseef, F. (2019). Developing a prediction model to predict the construction project cost by using multiple linear regression technique. Indian Journal of Science and Technology, 12(7), 1–6. https://doi.org/10.17485/ijst/2019/v12i7/138685
   Google Scholar
• Mcenroe, B. M. (2007, February). Final report sizing of highway culverts and bridges: A historical review of methods and criteria. Kansas Department of Transportation.
   Google Scholar
• Meharie, M. G., & Gariy, Z. A. (2021). Application of stacking ensemble machine learning algorithm in predicting the cost of highway construction projects. Engineering, Construction and Architectural Management, 29(7), pp. 2836–2853. https://doi.org/10.1108/ECAM-02-2020-0128
   Google Scholar
• Meharie, M. G., & Shaik, N. (2020). Predicting highway construction costs : Comparison of the performance of random forest, neural network and support vector machine models. Journal of Soft Computing in Civil Engineering, 2, 103–112.
   Google Scholar
• Mohammed, F., Al-Zwainy, S., & Hadhal, N. T. (2016). Building a mathematical model for predicting the cost of the communication towers projects using multifactor linear regression technique. International Journal of Construction Engineering and Management, 5(1), 25–29. http://journal.sapub.org/ijcem
   Google Scholar
• Mumela, M. E., Christine, N., Limited, R. E., & Box, P. O. (2017). Effect of contractor knowledge and experience on cost estimation in plant infrastructure projects in Kenya. International Journal of Science and Research (IJSR), 6(6), 2460–2466. https://doi.org/10.21275/ART20174864
   Google Scholar
• Narbaev, T., Hazir, Ö., Khamitova, B., & Talgat, S. (2023). A machine learning study to improve the reliability of project cost estimates. International Journal of Production Research, 61, 1–18. https://doi.org/10.1080/00207543.2023.2262051
   Google Scholar
• Operations, R. (2020, December). Cost estimating manual for projects. Washington State Department of Transportation’s (WSDOT).
   Google Scholar
• Profile, S. E. E. (2015). Manipulation theory of inflation: A research study on components of general price rise manipulation theory of inflation. PRAGATI: Journal of Indian Economy, 1(2), 66–82. https://doi.org/10.17492/pragati.v1i2.2507
   Google Scholar
• Ravindran, H. (2018). Cost prediction model for building construction projects. International Journal of Innovative Science and Research Technology, 3(4), 448–449.
   Google Scholar
• Saeidlou, S., & Ghadiminia, N. (2023). A construction cost estimation framework using DNN and validation unit. Building Research and Information, 0(0), 1–11. https://doi.org/10.1080/09613218.2023.2196388
   Google Scholar
• Sarode, G. C., & Chandgude, S. E. (2020). A review on cost prediction analysis of construction project using ANN model. International Journal of Innovative Research in Science, Engineering and Technology (IJIRSET), 9(4), 1516–1524.
   Google Scholar
• Shaban, A., Khawlie, M., Kheir, R. B., & Abdallah, C. (2017). Assessment of road instability along a typical mountainous road using GIS and aerial photos, Lebanon ± eastern Mediterranean. Bulletin of the International Association of Engineering Geology,60, 93–101. https://doi.org/10.1007/BF02595036
   Google Scholar
• Son, P. V. H., Duy, N. H. C., & Dat, P. T. (2021). Optimization of construction material cost through logistics planning model of dragonfly algorithm—Particle swarm optimization. KSCE Journal of Civil Engineering, 25(7), 2350–2359. https://doi.org/10.1007/s12205-021-1427-5
   Web of Science ®Google Scholar
• Son, P. V. H., & Khoi, L. N. Q. (2023a). Multi-modal optimization for time–cost–quality–work continuity trade-off in construction projects using a hybrid based on SMA and M&C. Asian Journal of Civil Engineering, 147, 110–775. https://doi.org/10.1007/s42107-023-00880-2
   Google Scholar
• Son, P. V. H., & Nguyen Dang, N. T. (2023). Optimizing time and cost simultaneously in projects with multi-verse optimizer. Asian Journal of Civil Engineering, 24(7), 2443–2449. https://doi.org/10.1007/s42107-023-00652-y
   Google Scholar
• Sonmez, R., & Ontepeli, B. (2010). Predesign cost estimation of urban railway projects with parametric modeling. Journal of Civil Engineering and Management, 15(4), 405–409. https://doi.org/10.3846/1392-3730.2009.15.405-409
   Google Scholar
• Swei, O., Gregory, J., & Kirchain, R. (2017). Construction cost estimation: A parametric approach for better estimates of expected cost and variation. Transportation Research Part B: Methodological, 101, 295–305. https://doi.org/10.1016/j.trb.2017.04.013
   Web of Science ®Google Scholar
• Tadesse, N., & Dinku, A. (2017). Conceptual cost estimation of road projects in Ethiopia using neural networks. Journal of the European Economic Association, 35, 17–29.
   Google Scholar
• Taherdoost, H. (2017). Validity and reliability of the research instrument; how to test the validation of a questionnaire/survey in a research. International Journal of Academic Research in Management (IJARM). https://doi.org/10.2139/ssrn.3205040
   Google Scholar
• Tayefeh Hashemi, S., Ebadati, O. M., & Kaur, H. (2020). Cost estimation and prediction in construction projects: A systematic review on machine learning techniques. SN Applied Sciences, 2(10), 1–27. https://doi.org/10.1007/s42452-020-03497-1
   Web of Science ®Google Scholar
• Thomas, N., & Thomas, A. V. (2017). Regression modelling for prediction of construction cost and duration. Applied Mechanics and Materials, 857, 195–199. https://doi.org/10.4028/www.scientific.net/AMM.857.195
   Google Scholar
• Velumani, P., & Nampoothiri, N. V. N. (2019). Analysis of construction cost prediction studies-global perspective. International Review of Applied Sciences and Engineering, 10(3), 275–281. https://doi.org/10.1556/1848.2019.0032
   Google Scholar
• Vijay, B. G., Rudraswamy, C. K., & Khatawkar, R. (2020). Study on impact of gradient on capacity of two lane undivided national highways. Bannerghatta Biological Park.
   Google Scholar
• Wang, Y., Ning, X., Zhen, D., Yong, W., & Zhang, H. (2023). Research on construction project cost prediction model based on recurrent neural network. SHS Web of Conferences, 170, 02009. https://doi.org/10.1051/shsconf/202317002009
   Google Scholar
• Williams, R. C., & Songer, A. D. (2008). The development of mathematical models for preliminary prediction of highway construction duration. (Doctoral dissertation, Virginia Tech).
   Google Scholar
• Xiong, B. (2016). Improving cost estimation performance: An investigation of prediction technique and person - environment interaction (Doctoral dissertation, Queensland University of Technology).
   Google Scholar
• Zuber, S., Nawi, M., & Abdul Nifa, B. (2018, December). An overview of project delivery methods in construction industry. International Journal of Supply Chain Management (IJSCM).
   Google Scholar