How to cite this paper
Ghazimoradi, M., Kheyroddin, A & Rezayfar, O. (2016). Diagnosing the success of the construction projects during the initial phases.Decision Science Letters , 5(3), 395-406.
Refrences
Atkinson, R. (1999). Project management: cost, time and quality, two best guesses and a phenomenon, its time to accept other success criteria.International journal of project management, 17(6), 337-342.
Bygballe, L. E., Jahre, M., & Sw?rd, A. (2010). Partnering relationships in construction: A literature review. Journal of purchasing and supply management, 16(4), 239-253.
Chang, A., Chih, Y. Y., Chew, E., & Pisarski, A. (2013). Reconceptualising mega project success in Australian Defence: Recognising the importance of value co-creation. International Journal of Project Management, 31(8), 1139-1153.
Cheung, S. O., Wong, P. S. P., Fung, A. S., & Coffey, W. V. (2006). Predicting project performance through neural networks. International Journal of Project Management, 24(3), 207-215.
Cheung, S. O., Yiu, T. W., & Chan, H. W. (2009). Exploring the potential for predicting project dispute resolution satisfaction using logistic regression.Journal of Construction Engineering and Management, 136(5), 508-517.
Chua, D. K. H., Loh, P. K., Kog, Y. C., & Jaselskis, E. J. (1997). Neural networks for construction project success. Expert Systems with Applications,13(4), 317-328.
Davis, K. (2014). Different stakeholder groups and their perceptions of project success. International Journal of Project Management, 32(2), 189-201.
Eigbe, A. P., Sauser, B. J., & Felder, W. (2015). Systemic analysis of the critical dimensions of project management that impact test and evaluation program outcomes. International Journal of Project Management, 33(4), 747-759.
Eigbe, A. P., Sauser, B. J., & Felder, W. (2015). Systemic analysis of the critical dimensions of project management that impact test and evaluation program outcomes. International Journal of Project Management, 33(4), 747-759.
Han, S. H., Kim, D. Y., & Kim, H. (2007). Predicting profit performance for selecting candidate international construction projects. Journal of Construction Engineering and Management, 133(6), 425-436.
Hwang, S. (2009). Dynamic regression models for prediction of construction costs. Journal of Construction Engineering and Management, 135(5), 360-367.
Hwang, S. (2011). Time series models for forecasting construction costs using time series indexes. Journal of Construction Engineering and Management,137(9), 656-662.
Kim, B. C., & Reinschmidt, K. F. (2010). Probabilistic forecasting of project duration using Kalman filter and the earned value method. Journal of Construction Engineering and Management, 136(8), 834-843.
Ko, C. H., & Cheng, M. Y. (2007). Dynamic prediction of project success using artificial intelligence. Journal of construction engineering and management,133(4), 316-324.
Lam, E. W., Chan, A. P., & Chan, D. W. (2008). Determinants of successful design-build projects. Journal of Construction Engineering and management,134(5), 333-341.
Ika, L. A. (2009). Project success as a topic in project management journals.Project Management Journal, 40(4), 6-19.
Li, J., Moselhi, O., & Alkass, S. (2006). Forecasting project status by using fuzzy logic. Journal of construction engineering and management, 132(11), 1193-1202.
Lipke, W., Zwikael, O., Henderson, K., & Anbari, F. (2009). Prediction of project outcome: The application of statistical methods to earned value management and earned schedule performance indexes. International journal of project management, 27(4), 400-407.
Petro, Y., & Gardiner, P. (2015). An investigation of the influence of organizational design on project portfolio success, effectiveness and business efficiency for project-based organizations. International Journal of Project Management, 33(8), 1717-1729.
Wang, Y. R., & Gibson, G. E. (2010). A study of preproject planning and project success using ANNs and regression models. Automation in Construction, 19(3), 341-346.
De Wit, A. (1988). Measurement of project success. International journal of project management, 6(3), 164-170.
Wong, P. S., On Cheung, S., & Hardcastle, C. (2007). Embodying learning effect in performance prediction. Journal of construction engineering and management, 133(6), 474-482.
Young, R., & Poon, S. (2013). Top management support—almost always necessary and sometimes sufficient for success: Findings from a fuzzy set analysis. International journal of project management, 31(7), 943-957.
Bygballe, L. E., Jahre, M., & Sw?rd, A. (2010). Partnering relationships in construction: A literature review. Journal of purchasing and supply management, 16(4), 239-253.
Chang, A., Chih, Y. Y., Chew, E., & Pisarski, A. (2013). Reconceptualising mega project success in Australian Defence: Recognising the importance of value co-creation. International Journal of Project Management, 31(8), 1139-1153.
Cheung, S. O., Wong, P. S. P., Fung, A. S., & Coffey, W. V. (2006). Predicting project performance through neural networks. International Journal of Project Management, 24(3), 207-215.
Cheung, S. O., Yiu, T. W., & Chan, H. W. (2009). Exploring the potential for predicting project dispute resolution satisfaction using logistic regression.Journal of Construction Engineering and Management, 136(5), 508-517.
Chua, D. K. H., Loh, P. K., Kog, Y. C., & Jaselskis, E. J. (1997). Neural networks for construction project success. Expert Systems with Applications,13(4), 317-328.
Davis, K. (2014). Different stakeholder groups and their perceptions of project success. International Journal of Project Management, 32(2), 189-201.
Eigbe, A. P., Sauser, B. J., & Felder, W. (2015). Systemic analysis of the critical dimensions of project management that impact test and evaluation program outcomes. International Journal of Project Management, 33(4), 747-759.
Eigbe, A. P., Sauser, B. J., & Felder, W. (2015). Systemic analysis of the critical dimensions of project management that impact test and evaluation program outcomes. International Journal of Project Management, 33(4), 747-759.
Han, S. H., Kim, D. Y., & Kim, H. (2007). Predicting profit performance for selecting candidate international construction projects. Journal of Construction Engineering and Management, 133(6), 425-436.
Hwang, S. (2009). Dynamic regression models for prediction of construction costs. Journal of Construction Engineering and Management, 135(5), 360-367.
Hwang, S. (2011). Time series models for forecasting construction costs using time series indexes. Journal of Construction Engineering and Management,137(9), 656-662.
Kim, B. C., & Reinschmidt, K. F. (2010). Probabilistic forecasting of project duration using Kalman filter and the earned value method. Journal of Construction Engineering and Management, 136(8), 834-843.
Ko, C. H., & Cheng, M. Y. (2007). Dynamic prediction of project success using artificial intelligence. Journal of construction engineering and management,133(4), 316-324.
Lam, E. W., Chan, A. P., & Chan, D. W. (2008). Determinants of successful design-build projects. Journal of Construction Engineering and management,134(5), 333-341.
Ika, L. A. (2009). Project success as a topic in project management journals.Project Management Journal, 40(4), 6-19.
Li, J., Moselhi, O., & Alkass, S. (2006). Forecasting project status by using fuzzy logic. Journal of construction engineering and management, 132(11), 1193-1202.
Lipke, W., Zwikael, O., Henderson, K., & Anbari, F. (2009). Prediction of project outcome: The application of statistical methods to earned value management and earned schedule performance indexes. International journal of project management, 27(4), 400-407.
Petro, Y., & Gardiner, P. (2015). An investigation of the influence of organizational design on project portfolio success, effectiveness and business efficiency for project-based organizations. International Journal of Project Management, 33(8), 1717-1729.
Wang, Y. R., & Gibson, G. E. (2010). A study of preproject planning and project success using ANNs and regression models. Automation in Construction, 19(3), 341-346.
De Wit, A. (1988). Measurement of project success. International journal of project management, 6(3), 164-170.
Wong, P. S., On Cheung, S., & Hardcastle, C. (2007). Embodying learning effect in performance prediction. Journal of construction engineering and management, 133(6), 474-482.
Young, R., & Poon, S. (2013). Top management support—almost always necessary and sometimes sufficient for success: Findings from a fuzzy set analysis. International journal of project management, 31(7), 943-957.