| Peer-Reviewed

Improving Risk Decisions for Internationally Contracting Projects Based on Behavioral Decision Theory

Received: 9 January 2017    Accepted: 23 January 2017    Published: 20 February 2017
Views:       Downloads:
Abstract

Project risks have been proposed to be divided into four categories, namely, strategic risks, financial risks, operational risks and hazard risks for projects under the international competitive environment. Through systematical studies on internationally contracting project risk decisions based on Behavioral Decision Theory (BDT), key factors related to the behavior preferences of decision makers have been induced to expand and improve existing risk decision models, improving the efficiency and effectiveness of risk decision-making. Such systematical studies have resulted in some interesting findings which may be helpful for guiding the project management in strategic and operational planning. The first finding shows that, a reasonable guide has helped owners determine the appropriate contracting project management mode based on the specific context and requirements of the project in order to better improve the decision-making efficiency and effectiveness, and effectively control project risks by properly staffing the organizational behaviors. The second finding shows that, the risk quantification and proper financing decision making basis has been proposed on internationally contracting project costs estimate to meet the financing requirements of international banks, so as to help the contractor assist the owners for financing. The third finding shows that, the clearly defined methods for calculating the expected returns and risks on the risk decision on contracting project in properly packaging planning and procurement strategies have been systematically studied, so as to effectively instruct the contractors for the project subcontracting and its packaging planning and risk controlling.

Published in American Journal of Data Mining and Knowledge Discovery (Volume 2, Issue 2)
DOI 10.11648/j.ajdmkd.20170202.11
Page(s) 42-49
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Project Management, Project Strategic Planning, Risk Decision, Behavioral Decision Theory

References
[1] Hetogh, M., Baker, S., Staal-Ong, P., & Westerveld, E. (2008). Managing Large Infrastructure Projects-Research on Best Practices and Lessons Learned in Large Infrastructure Projects in Europe. AT Osborne BV.
[2] Simon, H. (1955). A behavioral model of rational choice. The quarterly journal of economics, 99-118.
[3] Simon, H. (1982). Models of bounded rationality: Empirically grounded economic reason, Massachusetts, MIT press.
[4] Sterman, J., Henderson, R., Beinhocker, E. (2007). Getting big too fast: strategic dynamics with increasing returns and bounded rationality. Management Science, 53(4): 683-696.
[5] Chen, Y., Su, X., Zhao, X. (2012). Modeling bounded rationality in capacity allocation games with the quantal response equilibrium. Management Science, 58(10): 1952-1962.
[6] Harstad, R., & Selten, R. (2013). Bounded-rationality models: tasks to become intellectually competitive. Journal of Economic Literature, 51(2): 496-511.
[7] Jacobs, B., & Wright, R. (2010). Bounded rationality, retaliation, and the spread of urban violence. Journal of Interpersonal Violence, 25(10): 1739-1766.
[8] Edwards, W. (1961). Behavioral decision theory. Annual Review of Psychology, 7, (12): 473-498.
[9] Kahneman, D., & Tversky A. (1979). Prospect theory: an analysis of decision under risk. Econometrica, 47: 263-291.
[10] Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Risk Uncertainty, 5: 297-323.
[11] Wong, K. (2011). Regret theory and the banking firm: the optimal bank interest margin. Economic Modeling, 28(6): 2483-2487.
[12] Bui, M., Krishen, A., Bates, K. (2011). Modeling regret effects on consumer post-purchase decisions. European Journal of Marketing, 45(7/8): 1068-1090.
[13] Bromiley, P. (2009). A prospect theory model of resource allocation. Decision Analysis, 6(3): 124-138.
[14] Liu, P., Jin, F., Zhang, X. (2011). Research on the multi-attribute decision-making under risk with interval probability based on prospect theory and the uncertain linguistic variables. Knowledge-Based Systems, 24(4): 554-561.
[15] Graham, M., Winch, G. (2010). Managing Construction Project. Blackwell Science Ltd.
[16] Maytorena, E., Winch, G., Freeman, J. (2007). The Influence of experience and information search styles on project risk identification performance. IEEE Transactions on Engineering Management, 54(2):315-326.
[17] Rubio, R., Ivan, L., Alfonso, P. (2012). Identification of causes of risk in the management of large construction projects in Spain. DYNA, 87(6):689-697.
[18] Choudhry, R., & Khurram, I. (2013). Identification of risk management system in construction industry in Pakistan. Journal of Management in Engineering, 29(1):42-49.
[19] Thevendran, V., & Mawdesley, M. J. (2004). Perception of human risk factors in construction projects. International Journal of Project Management, 22(2): 131-137.
[20] Hsueh, S., Perng, Y., Yan, M., Lee, J. (2007). On-line multi-criterion risk assessment model for construction joint ventures in China. Automation in Construction, 16(5):607-619.
[21] Nieto-Morote, A., & Ruz-Vila, F. (2012). A fuzzy multi-criteria decision-making model for construction contractor prequalification. Automation in Construction, 25:8-19.
[22] Vanhoucke, M. (2011). On the dynamic use of project performance and schedule risk information during project tracking. Omega, 39 (4):416-426.
[23] Zeng, J., An, M., Smith, N. (2007). Application of a fuzzy based decision making methodology to construction project risk assessment. International Journal of Project Management, 25(6):589-600.
[24] Fahad, A., Bhamra, R., Salman, A. (2014). Risk management framework for build, operate and transfer (BOT) projects in Kuwait. Journal of civil engineering and management, 20(3):415-433.
[25] Melnic, A. (2010). Risk response strategies in project management. Metalurgia International, 15(8): 74-78.
[26] Vanhoucke, M. (2012). Measuring the efficiency of project control using fictitious and empirical project data. International Journal of Project Management, 30 (2):252- 263.
[27] Charrel, P., & Galarreta, D. (2007). Project Management and Risk Management in Complex Projects. England Springer.
[28] Javernick-Will, L., & Levitt, R. (2010). Mobilizing institutional knowledge for international projects. Journal of Construction Engineering and Management, 36(4):430-440
[29] Dikmen, I., Birgonul, M., & Gur, A. (2007). A case-based decision support tool for bid mark-up estimation of international construction projects. Automation in Construction, 17(1): 30-44.
[30] Robert, B, Young, R.&Javalgi, R. (2007). International marketing research: A global project management perspective. Business Horizons, 50(2):113–122.
[31] Hashemi, H., Meysam, M., Tavakkoli-Moghaddam, T., Gholipour, Y. (2013). Compromise ranking approach with bootstrap confidence intervals for risk assessment in port management projects. Journal of Management in Engineering, 29(1):334-344.
[32] Sousa, R., & Einstein. H. (2012). Risk analysis during tunnel construction using Bayesian networks: Porto metro case study. Tunneling and Underground Space Technology, 2012, 27, 86-100.
[33] Mehmedali, E., Abdulrezak, N. (2007). A framework for contractors to reach strategically correct bid/no bid and mark-up size decisions. Building and Environment, 42(3):1373-1385.
[34] Nieto-Morote, A., & Ruz-Vila, F. (2011). A fuzzy approach to construction project risk assessment. International Journal of Project Management, 29(2):220-231.
[35] Botin, J., Ronald, R., Martin, L. (2011). Methodological model to assist in the optimization and risk management of mining investment decisions. DYNA, 78(170): 221-226.
[36] Nikolić, D., Jednaka, S., Benkovića, S., Poznanić, V. (2011). Project finance risk evaluation of the electric power industry of Serbia. Energy Policy, 39(10): 6168-6177.
[37] Loosemore, M., & McCarthy, C. (2008). Perceptions of contractual risk allocation in construction supply chains. Journal of Professional Issues in Engineering Education and Practice, 134(1): 95-105.
[38] Khattab, A., Anchor, J., Davies, E. (2007). Managerial perceptions of political risk in international projects. International Journal of Project Management, 25(7):734-743.
[39] Holburn, G., & Zelner, B. (2010). Political capabilities, policy risk, and international investment strategy: evidence from the global electric power generation industry. Strategic Management Journal, 31:1290-1315.
[40] Jia, Z. (2013). Risk management of international project based on AHP and FMEA. Applied Mechanics and Materials, 8: 357-360.
[41] Kerzner, H. (2006). Project Management-A Systems Approach to Planning, Scheduling, and Controlling (9th Edition), Hoboken, New Jersey: John Wiley & Sons, Inc.
Cite This Article
  • APA Style

    Zhenyou Li. (2017). Improving Risk Decisions for Internationally Contracting Projects Based on Behavioral Decision Theory. American Journal of Data Mining and Knowledge Discovery, 2(2), 42-49. https://doi.org/10.11648/j.ajdmkd.20170202.11

    Copy | Download

    ACS Style

    Zhenyou Li. Improving Risk Decisions for Internationally Contracting Projects Based on Behavioral Decision Theory. Am. J. Data Min. Knowl. Discov. 2017, 2(2), 42-49. doi: 10.11648/j.ajdmkd.20170202.11

    Copy | Download

    AMA Style

    Zhenyou Li. Improving Risk Decisions for Internationally Contracting Projects Based on Behavioral Decision Theory. Am J Data Min Knowl Discov. 2017;2(2):42-49. doi: 10.11648/j.ajdmkd.20170202.11

    Copy | Download

  • @article{10.11648/j.ajdmkd.20170202.11,
      author = {Zhenyou Li},
      title = {Improving Risk Decisions for Internationally Contracting Projects Based on Behavioral Decision Theory},
      journal = {American Journal of Data Mining and Knowledge Discovery},
      volume = {2},
      number = {2},
      pages = {42-49},
      doi = {10.11648/j.ajdmkd.20170202.11},
      url = {https://doi.org/10.11648/j.ajdmkd.20170202.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajdmkd.20170202.11},
      abstract = {Project risks have been proposed to be divided into four categories, namely, strategic risks, financial risks, operational risks and hazard risks for projects under the international competitive environment. Through systematical studies on internationally contracting project risk decisions based on Behavioral Decision Theory (BDT), key factors related to the behavior preferences of decision makers have been induced to expand and improve existing risk decision models, improving the efficiency and effectiveness of risk decision-making. Such systematical studies have resulted in some interesting findings which may be helpful for guiding the project management in strategic and operational planning. The first finding shows that, a reasonable guide has helped owners determine the appropriate contracting project management mode based on the specific context and requirements of the project in order to better improve the decision-making efficiency and effectiveness, and effectively control project risks by properly staffing the organizational behaviors. The second finding shows that, the risk quantification and proper financing decision making basis has been proposed on internationally contracting project costs estimate to meet the financing requirements of international banks, so as to help the contractor assist the owners for financing. The third finding shows that, the clearly defined methods for calculating the expected returns and risks on the risk decision on contracting project in properly packaging planning and procurement strategies have been systematically studied, so as to effectively instruct the contractors for the project subcontracting and its packaging planning and risk controlling.},
     year = {2017}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - Improving Risk Decisions for Internationally Contracting Projects Based on Behavioral Decision Theory
    AU  - Zhenyou Li
    Y1  - 2017/02/20
    PY  - 2017
    N1  - https://doi.org/10.11648/j.ajdmkd.20170202.11
    DO  - 10.11648/j.ajdmkd.20170202.11
    T2  - American Journal of Data Mining and Knowledge Discovery
    JF  - American Journal of Data Mining and Knowledge Discovery
    JO  - American Journal of Data Mining and Knowledge Discovery
    SP  - 42
    EP  - 49
    PB  - Science Publishing Group
    SN  - 2578-7837
    UR  - https://doi.org/10.11648/j.ajdmkd.20170202.11
    AB  - Project risks have been proposed to be divided into four categories, namely, strategic risks, financial risks, operational risks and hazard risks for projects under the international competitive environment. Through systematical studies on internationally contracting project risk decisions based on Behavioral Decision Theory (BDT), key factors related to the behavior preferences of decision makers have been induced to expand and improve existing risk decision models, improving the efficiency and effectiveness of risk decision-making. Such systematical studies have resulted in some interesting findings which may be helpful for guiding the project management in strategic and operational planning. The first finding shows that, a reasonable guide has helped owners determine the appropriate contracting project management mode based on the specific context and requirements of the project in order to better improve the decision-making efficiency and effectiveness, and effectively control project risks by properly staffing the organizational behaviors. The second finding shows that, the risk quantification and proper financing decision making basis has been proposed on internationally contracting project costs estimate to meet the financing requirements of international banks, so as to help the contractor assist the owners for financing. The third finding shows that, the clearly defined methods for calculating the expected returns and risks on the risk decision on contracting project in properly packaging planning and procurement strategies have been systematically studied, so as to effectively instruct the contractors for the project subcontracting and its packaging planning and risk controlling.
    VL  - 2
    IS  - 2
    ER  - 

    Copy | Download

Author Information
  • Department of Project Management, China NERIN Engineering Co. Ltd., Nanchang, China

  • Sections