How to cite this paper
Albogami, S., Ariffin, M., Supeni, E & Ahmad, K. (2022). Development of a hybrid AHP and Dempster-Shafer theory of evidence for project risk assessment problem.Journal of Project Management, 7(2), 77-94.
Refrences
Abd El-Karim, M. S. B. A., Mosa El Nawawy, O. A., & Abdel-Alim, A. M. (2017). Identification and assessment of risk factors affecting construction projects. HBRC Journal, 13(2), 202-216.
Ansarifar, J., Tavakkoli-Moghaddam, R., Akhavizadegan, F., & Hassanzadeh Amin, S. (2018) Multi-objective integrated planning and scheduling model for operating rooms under uncertainty. Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine, 232(9), 930-948.
Абдикеев, Н. М., Богачев, Ю. С., & Бекулова, С. Р. (2019). Инвестиционный потенциал обрабатывающей промышленности. Финансы: Теория и Практика, 23(4).
Ballent, W., Corotis, R. B., & Torres-Machi, C. (2019). Representing uncertainty in natural hazard risk assessment with Dempster Shafer (Evidence) theory. Sustainable and Resilient Infrastructure, 4(4), 137-151.
Bowers, J., & Khorakian, A. (2014). Integrating risk management in the innovation project. European Journal of innovation management, 17(1), 25-40.
Brustbauer, J. (2016). Enterprise risk management in SMEs: Towards a structural model. International Small Business Journal, 34(1), 70-85.
Carvalho, M. M. d., & Rabechini Junior, R. (2015). Impact of risk management on project performance: the importance of soft skills. International Journal of Production Research, 53(2), 321-340.
Chemweno, P., Pintelon, L., Van Horenbeek, A., & Muchiri, P. (2015). Development of a risk assessment selection methodology for asset maintenance decision making: An analytic network process (ANP) approach. International Journal of Production Economics, 170, 663-676.
Dašić, B., Trklja, R., & Savić, M. (2019). Comparative analysis of inflows and sectoral distribution of the foreign direct investments flows. Mining and Metallurgy Engineering Bor(1-2), 31-40.
Davari, M., & Demeulemeester, E. (2019). The proactive and reactive resource-constrained project scheduling problem. Journal of Scheduling, 22(2), 211-237.
DELGOSHAEI, A. (2016). SCHEDULING DYNAMIC CELLULAR MANUFACTURING SYSTEMS IN THE PRESENCE OF COST UNCERTAINTY USING HEURISTIC METHOD.
Delgoshaei, A., & Gomes, C. (2016). A multi-layer perceptron for scheduling cellular manufacturing systems in the presence of unreliable machines and uncertain cost. Applied Soft Computing, 49, 27-55.
Delgoshaei, A., Rabczuk, T., Ali, A., & Ariffin, M. K. A. (2017). An applicable method for modifying over-allocated multi-mode resource constraint schedules in the presence of preemptive resources. Annals of Operations Research, 259(1-2), 85-117.
Dziadosz, A., & Rejment, M. (2015). Risk analysis in construction project-chosen methods. Procedia Engineering, 122, 258-265.
Esmaeili, B., Hallowell, M. R., & Rajagopalan, B. (2015a). Attribute-based safety risk assessment. I: Analysis at the fundamental level. Journal of Construction Engineering and Management, 141(8), 04015021
Esmaeili, B., Hallowell, M. R., & Rajagopalan, B. (2015b) Attribute-based safety risk assessment. II: Predicting safety outcomes using generalized linear models. Journal of Construction Engineering and Management, 141(8), 04015022.
Fabricius, G., & Büttgen, M. (2015). Project managers' overconfidence: how is risk reflected in anticipated project success? Business Research, 8(2), 239-263.
Fang, C., Marle, F., & Xie, M. (2016). Applying importance measures to risk analysis in engineering project using a risk network model. IEEE Systems Journal, 11(3), 1548-1556.
Grabovy, P., & Orlov, A. (2016). The overall risk assessment and management: implementation of foreign investment construction megaprojects by Russian development companies. Procedia Engineering, 153, 195-202.
Gutjahr, W. J. (2015). Bi-objective multi-mode project scheduling under risk aversion. European Journal of Operational Research, 246(2), 421-434.
Hatefi, S. M., Basiri, M. E., & Tamošaitienė, J. (2019). An evidential model for environmental risk assessment in projects using dempster–shafer theory of evidence. Sustainability, 11(22), 6329.
Hossen, M. M., Kang, S., & Kim, J. (2015). Construction schedule delay risk assessment by using combined AHP-RII methodology for an international NPP project. Nuclear Engineering and Technology, 47(3), 362-379.
Islam, M. S., Nepal, M. P., Skitmore, M., & Attarzadeh, M. (2017). Current research trends and application areas of fuzzy and hybrid methods to the risk assessment of construction projects. Advanced Engineering Informatics, 33, 112-131
Kim, B.-C. (2015). Integrating risk assessment and actual performance for probabilistic project cost forecasting: a second moment Bayesian model. IEEE Transactions on Engineering Management, 62(2), 158-170.
Kokangül, A., Polat, U., & Dağsuyu, C. (2017). A new approximation for risk assessment using the AHP and Fine Kinney methodologies. Safety Science, 91, 24-32.
Kuo, Y.-C., & Lu, S.-T. (2013). Using fuzzy multiple criteria decision making approach to enhance risk assessment for metropolitan construction projects. International Journal of Project Management, 31(4), 602-614.
Leu, S.-S., & Chang, C.-M. (2013). Bayesian-network-based safety risk assessment for steel construction projects. Accident Analysis & Prevention, 54, 122-133.
Li, Z., Wen, G., & Xie, N. (2015). An approach to fuzzy soft sets in decision making based on grey relational analysis and Dempster–Shafer theory of evidence: An application in medical diagnosis. Artificial Intelligence in Medicine, 64(3), 161-171.
Liu, J., Jin, F., Xie, Q., & Skitmore, M. (2017). Improving risk assessment in financial feasibility of international engineering projects: A risk driver perspective. International Journal of Project Management, 35(2), 204-211.
Marcelino-Sádaba, S., Pérez-Ezcurdia, A., Lazcano, A. M. E., & Villanueva, P. (2014). Project risk management methodology for small firms. International Journal of Project Management, 32(2), 327-340.
Muriana, C., & Vizzini, G. (2017). Project risk management: A deterministic quantitative technique for assessment and mitigation. International Journal of Project Management, 35(3), 320-340.
Nasrabadi, M., & Mirzazadeh, A. (2016). The inventory system management under uncertain conditions and time value of money. International Journal of Supply and Operations Management, 3(1), 1192-1214.
Niazi, M., Mahmood, S., Alshayeb, M., Riaz, M. R., Faisal, K., Cerpa, N., . . . Richardson, I. (2016) Challenges of project management in global software development: A client-vendor analysis. Information and Software Technology, 80, 1-19.
Pan, Y., Zhang, L., Li, Z., & Ding, L. (2019). Improved fuzzy Bayesian network-based risk analysis with interval-valued fuzzy sets and D–S evidence theory. IEEE Transactions on Fuzzy Systems, 28(9), 2063-2077.
Qazi, A., Quigley, J., Dickson, A., & Kirytopoulos, K. (2016). Project Complexity and Risk Management (ProCRiM): Towards modelling project complexity driven risk paths in construction projects. International Journal of Project Management, 34(7), 1183-1198.
Sangaiah, A. K., Samuel, O. W., Li, X., Abdel-Basset, M., & Wang, H. (2018). Towards an efficient risk assessment in software projects–Fuzzy reinforcement paradigm. Computers & Electrical Engineering, 71, 833-846.
Suresh, K., & Dillibabu, R. (2020). A novel fuzzy mechanism for risk assessment in software projects. Soft Computing, 24(3), 1683-1705.
Tang, H. (2015). A novel fuzzy soft set approach in decision making based on grey relational analysis and Dempster–Shafer theory of evidence. Applied Soft Computing, 31, 317-325.
Tao, S., Wu, C., Sheng, Z., & Wang, X. (2018). Space-time repetitive project scheduling considering location and congestion. Journal of Computing in Civil Engineering, 32(3), 04018017.
Tonmoy, F. N., Wainwright, D., Verdon-Kidd, D. C., & Rissik, D. (2018). An investigation of coastal climate change risk assessment practice in Australia. Environmental Science & Policy, 80, 9-20.
Valipour, A., Yahaya, N., Md Noor, N., Antuchevičienė, J., & Tamošaitienė, J. (2017). Hybrid SWARA-COPRAS method for risk assessment in deep foundation excavation project: An Iranian case study. Journal of Civil Engineering and Management, 23(4), 524-532.
Wang, C. M., Xu, B. B., Zhang, S. J., & Chen, Y. Q. (2016). Influence of personality and risk propensity on risk perception of Chinese construction project managers. International Journal of Project Management, 34(7), 1294-1304.
Wang, J., Hu, Y., Xiao, F., Deng, X., & Deng, Y. (2016). A novel method to use fuzzy soft sets in decision making based on ambiguity measure and Dempster–Shafer theory of evidence: an application in medical diagnosis. Artificial Intelligence in Medicine, 69, 1-11.
Williams, T. (2017). The nature of risk in complex projects. Project Management Journal, 48(4), 55-66.
Wu, D. D., Chen, S.-H., & Olson, D. L. (2014). Business intelligence in risk management: Some recent progresses. Information Sciences, 256, 1-7.
Yang, Y., Wang, J., Wang, G., & Chen, Y.-W. (2019). Research and development project risk assessment using a belief rule-based system with random subspaces. Knowledge-Based Systems, 178, 51-60.
Yet, B., Constantinou, A., Fenton, N., Neil, M., Luedeling, E., & Shepherd, K. (2016) A Bayesian network framework for project cost, benefit and risk analysis with an agricultural development case study. Expert Systems with Applications, 60, 141-155.
Zadeh, L. A. (1986). A simple view of the Dempster-Shafer theory of evidence and its implication for the rule of combination. A.I. Magazine, 7(2), 85-85.
Zavadskas, E. K., Turskis, Z., & Tamošaitiene, J. (2010). Risk assessment of construction projects. Journal of Civil Engineering and Management, 16(1), 33-46.
Zhang, Y. (2016). Selecting risk response strategies considering project risk interdependence. International Journal of Project Management, 34(5), 819-830.
Zhang, Y., & Fan, Z.-P. (2014). An optimization method for selecting project risk response strategies. International Journal of Project Management, 32(3), 412-422.
Zou, Y., Kiviniemi, A., & Jones, S. W. (2017). A review of risk management through BIM and BIM-related technologies. Safety Science, 97, 88-98.
Ansarifar, J., Tavakkoli-Moghaddam, R., Akhavizadegan, F., & Hassanzadeh Amin, S. (2018) Multi-objective integrated planning and scheduling model for operating rooms under uncertainty. Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine, 232(9), 930-948.
Абдикеев, Н. М., Богачев, Ю. С., & Бекулова, С. Р. (2019). Инвестиционный потенциал обрабатывающей промышленности. Финансы: Теория и Практика, 23(4).
Ballent, W., Corotis, R. B., & Torres-Machi, C. (2019). Representing uncertainty in natural hazard risk assessment with Dempster Shafer (Evidence) theory. Sustainable and Resilient Infrastructure, 4(4), 137-151.
Bowers, J., & Khorakian, A. (2014). Integrating risk management in the innovation project. European Journal of innovation management, 17(1), 25-40.
Brustbauer, J. (2016). Enterprise risk management in SMEs: Towards a structural model. International Small Business Journal, 34(1), 70-85.
Carvalho, M. M. d., & Rabechini Junior, R. (2015). Impact of risk management on project performance: the importance of soft skills. International Journal of Production Research, 53(2), 321-340.
Chemweno, P., Pintelon, L., Van Horenbeek, A., & Muchiri, P. (2015). Development of a risk assessment selection methodology for asset maintenance decision making: An analytic network process (ANP) approach. International Journal of Production Economics, 170, 663-676.
Dašić, B., Trklja, R., & Savić, M. (2019). Comparative analysis of inflows and sectoral distribution of the foreign direct investments flows. Mining and Metallurgy Engineering Bor(1-2), 31-40.
Davari, M., & Demeulemeester, E. (2019). The proactive and reactive resource-constrained project scheduling problem. Journal of Scheduling, 22(2), 211-237.
DELGOSHAEI, A. (2016). SCHEDULING DYNAMIC CELLULAR MANUFACTURING SYSTEMS IN THE PRESENCE OF COST UNCERTAINTY USING HEURISTIC METHOD.
Delgoshaei, A., & Gomes, C. (2016). A multi-layer perceptron for scheduling cellular manufacturing systems in the presence of unreliable machines and uncertain cost. Applied Soft Computing, 49, 27-55.
Delgoshaei, A., Rabczuk, T., Ali, A., & Ariffin, M. K. A. (2017). An applicable method for modifying over-allocated multi-mode resource constraint schedules in the presence of preemptive resources. Annals of Operations Research, 259(1-2), 85-117.
Dziadosz, A., & Rejment, M. (2015). Risk analysis in construction project-chosen methods. Procedia Engineering, 122, 258-265.
Esmaeili, B., Hallowell, M. R., & Rajagopalan, B. (2015a). Attribute-based safety risk assessment. I: Analysis at the fundamental level. Journal of Construction Engineering and Management, 141(8), 04015021
Esmaeili, B., Hallowell, M. R., & Rajagopalan, B. (2015b) Attribute-based safety risk assessment. II: Predicting safety outcomes using generalized linear models. Journal of Construction Engineering and Management, 141(8), 04015022.
Fabricius, G., & Büttgen, M. (2015). Project managers' overconfidence: how is risk reflected in anticipated project success? Business Research, 8(2), 239-263.
Fang, C., Marle, F., & Xie, M. (2016). Applying importance measures to risk analysis in engineering project using a risk network model. IEEE Systems Journal, 11(3), 1548-1556.
Grabovy, P., & Orlov, A. (2016). The overall risk assessment and management: implementation of foreign investment construction megaprojects by Russian development companies. Procedia Engineering, 153, 195-202.
Gutjahr, W. J. (2015). Bi-objective multi-mode project scheduling under risk aversion. European Journal of Operational Research, 246(2), 421-434.
Hatefi, S. M., Basiri, M. E., & Tamošaitienė, J. (2019). An evidential model for environmental risk assessment in projects using dempster–shafer theory of evidence. Sustainability, 11(22), 6329.
Hossen, M. M., Kang, S., & Kim, J. (2015). Construction schedule delay risk assessment by using combined AHP-RII methodology for an international NPP project. Nuclear Engineering and Technology, 47(3), 362-379.
Islam, M. S., Nepal, M. P., Skitmore, M., & Attarzadeh, M. (2017). Current research trends and application areas of fuzzy and hybrid methods to the risk assessment of construction projects. Advanced Engineering Informatics, 33, 112-131
Kim, B.-C. (2015). Integrating risk assessment and actual performance for probabilistic project cost forecasting: a second moment Bayesian model. IEEE Transactions on Engineering Management, 62(2), 158-170.
Kokangül, A., Polat, U., & Dağsuyu, C. (2017). A new approximation for risk assessment using the AHP and Fine Kinney methodologies. Safety Science, 91, 24-32.
Kuo, Y.-C., & Lu, S.-T. (2013). Using fuzzy multiple criteria decision making approach to enhance risk assessment for metropolitan construction projects. International Journal of Project Management, 31(4), 602-614.
Leu, S.-S., & Chang, C.-M. (2013). Bayesian-network-based safety risk assessment for steel construction projects. Accident Analysis & Prevention, 54, 122-133.
Li, Z., Wen, G., & Xie, N. (2015). An approach to fuzzy soft sets in decision making based on grey relational analysis and Dempster–Shafer theory of evidence: An application in medical diagnosis. Artificial Intelligence in Medicine, 64(3), 161-171.
Liu, J., Jin, F., Xie, Q., & Skitmore, M. (2017). Improving risk assessment in financial feasibility of international engineering projects: A risk driver perspective. International Journal of Project Management, 35(2), 204-211.
Marcelino-Sádaba, S., Pérez-Ezcurdia, A., Lazcano, A. M. E., & Villanueva, P. (2014). Project risk management methodology for small firms. International Journal of Project Management, 32(2), 327-340.
Muriana, C., & Vizzini, G. (2017). Project risk management: A deterministic quantitative technique for assessment and mitigation. International Journal of Project Management, 35(3), 320-340.
Nasrabadi, M., & Mirzazadeh, A. (2016). The inventory system management under uncertain conditions and time value of money. International Journal of Supply and Operations Management, 3(1), 1192-1214.
Niazi, M., Mahmood, S., Alshayeb, M., Riaz, M. R., Faisal, K., Cerpa, N., . . . Richardson, I. (2016) Challenges of project management in global software development: A client-vendor analysis. Information and Software Technology, 80, 1-19.
Pan, Y., Zhang, L., Li, Z., & Ding, L. (2019). Improved fuzzy Bayesian network-based risk analysis with interval-valued fuzzy sets and D–S evidence theory. IEEE Transactions on Fuzzy Systems, 28(9), 2063-2077.
Qazi, A., Quigley, J., Dickson, A., & Kirytopoulos, K. (2016). Project Complexity and Risk Management (ProCRiM): Towards modelling project complexity driven risk paths in construction projects. International Journal of Project Management, 34(7), 1183-1198.
Sangaiah, A. K., Samuel, O. W., Li, X., Abdel-Basset, M., & Wang, H. (2018). Towards an efficient risk assessment in software projects–Fuzzy reinforcement paradigm. Computers & Electrical Engineering, 71, 833-846.
Suresh, K., & Dillibabu, R. (2020). A novel fuzzy mechanism for risk assessment in software projects. Soft Computing, 24(3), 1683-1705.
Tang, H. (2015). A novel fuzzy soft set approach in decision making based on grey relational analysis and Dempster–Shafer theory of evidence. Applied Soft Computing, 31, 317-325.
Tao, S., Wu, C., Sheng, Z., & Wang, X. (2018). Space-time repetitive project scheduling considering location and congestion. Journal of Computing in Civil Engineering, 32(3), 04018017.
Tonmoy, F. N., Wainwright, D., Verdon-Kidd, D. C., & Rissik, D. (2018). An investigation of coastal climate change risk assessment practice in Australia. Environmental Science & Policy, 80, 9-20.
Valipour, A., Yahaya, N., Md Noor, N., Antuchevičienė, J., & Tamošaitienė, J. (2017). Hybrid SWARA-COPRAS method for risk assessment in deep foundation excavation project: An Iranian case study. Journal of Civil Engineering and Management, 23(4), 524-532.
Wang, C. M., Xu, B. B., Zhang, S. J., & Chen, Y. Q. (2016). Influence of personality and risk propensity on risk perception of Chinese construction project managers. International Journal of Project Management, 34(7), 1294-1304.
Wang, J., Hu, Y., Xiao, F., Deng, X., & Deng, Y. (2016). A novel method to use fuzzy soft sets in decision making based on ambiguity measure and Dempster–Shafer theory of evidence: an application in medical diagnosis. Artificial Intelligence in Medicine, 69, 1-11.
Williams, T. (2017). The nature of risk in complex projects. Project Management Journal, 48(4), 55-66.
Wu, D. D., Chen, S.-H., & Olson, D. L. (2014). Business intelligence in risk management: Some recent progresses. Information Sciences, 256, 1-7.
Yang, Y., Wang, J., Wang, G., & Chen, Y.-W. (2019). Research and development project risk assessment using a belief rule-based system with random subspaces. Knowledge-Based Systems, 178, 51-60.
Yet, B., Constantinou, A., Fenton, N., Neil, M., Luedeling, E., & Shepherd, K. (2016) A Bayesian network framework for project cost, benefit and risk analysis with an agricultural development case study. Expert Systems with Applications, 60, 141-155.
Zadeh, L. A. (1986). A simple view of the Dempster-Shafer theory of evidence and its implication for the rule of combination. A.I. Magazine, 7(2), 85-85.
Zavadskas, E. K., Turskis, Z., & Tamošaitiene, J. (2010). Risk assessment of construction projects. Journal of Civil Engineering and Management, 16(1), 33-46.
Zhang, Y. (2016). Selecting risk response strategies considering project risk interdependence. International Journal of Project Management, 34(5), 819-830.
Zhang, Y., & Fan, Z.-P. (2014). An optimization method for selecting project risk response strategies. International Journal of Project Management, 32(3), 412-422.
Zou, Y., Kiviniemi, A., & Jones, S. W. (2017). A review of risk management through BIM and BIM-related technologies. Safety Science, 97, 88-98.