Skip to main content

An FCM-based Dynamic Modeling of Operability and Maintainability Barriers in Road Projects

This article has been updated

Abstract

Building a new road infrastructure in the country leads to economic and industrial growth. A massive amount of money is paid by governments to build them; however, they fail due to many reasons related to operability and maintainability (O&M) issues. They are not also completed within the expected budget, time, and quality; so they are not justifiable. As these factors have a strong impact on projects, to reduce the final cost and other mentioned problems, it is necessary to identify the existing O&M barriers, their interrelationships, and their effects on the three mentioned factors. An in-depth literature review is conducted to identify the barriers. The fuzzy cognitive mapping (FCM) technique is used to model O&M barriers using real case data analyses. The findings reveal that managerial factors have more significanct impacts on the project’s success compared to other factors such as organizational, human resource, technology, and project management. Therefore, management methods are very important in developing integration in the project. Identifying, classifying, and determining the effects of barriers to entry of O&M contractors on the cost, time, and quality of road infrastructure projects show the signifcance of conducting this research, which is necessary to deal with the existing barriers. All these ultimately increase quality and reduce time and cost in road infrastructure projects.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2

Change history

  • 07 July 2021

    Change in first author's family name

References

  1. Ivanova, E., & Masarova, J. (2013). Importance of road infrastructure in the economic development and competitiveness. Economics and Management, 18(2), 263–274

    Google Scholar 

  2. Karim, H., & Magnosson, R. (2008). Road design for future maintenance problems and possibilities. Journal of Transportation Engineering, 134(12), 523–531

    Google Scholar 

  3. Justo-Silva, R., & Ferreira, A. (2019). Pavement maintenance considering traffic accident costs. International Journal of Pavement Research and Technology, 12(6), 562–573

    Google Scholar 

  4. Ramachandran, S., Rajendran, C., & Amirthalingam, V. (2019). Decision support system for the maintenance management of road network considering multi-criteria. International Journal of Pavement Research and Technology, 12(3), 325–335

    Google Scholar 

  5. Kordestani, N. (2018). Evaluating the barriers to the presence of operation and maintenance contractors in the pre-occupancy stages of infrastructure projects: a case study of road infrastructure projects. International Journal of Advanced Operations Management, 10(4), 345

    Google Scholar 

  6. Lichtig, W. (2006). The integrated agreement for lean project delivery. Constr Lawyer, 26(3), 25

    Google Scholar 

  7. Ahiaga-dagbui, DD. (2019). Reference class forecasting: a clear and present danger to cost-effective capital investment on major infrastructure projects.

  8. Johnson, R. M., & Babu, R. I. I. (2020). Time and cost overruns in the UAE construction industry: a critical analysis. International Journal of Construction Management, 20(5), 402–411

    Google Scholar 

  9. Eskandari, H., & Giger, C. D. (2008). A fast Pareto genetic algorithm approach for solving expensive multiobjective optimization problems. Journal of Heuristics, 14(3), 203–241

    MATH  Google Scholar 

  10. Saghatforoush, E., B. Trigunarsyah, Too, E. (2012). Assessment of operability and maintainability success factors in provision of extended constructability principles, in In 9th international congress on civil engineering. p. 1–10.

  11. Kahvandi, Z., et al. (2018). An FCM-based dynamic modelling of integrated project delivery implementation challenges in construction projects. Lean Construction Journal, 87, 63–87

    Google Scholar 

  12. Musta, A. (2019). Impact of risk analysis related to time, quality and cost in construction projects.

  13. Kordestani Ghalenoeei, N. (2018). Evaluating solutions to facilitate the presence of operation and maintenance contractors in the pre-occupancy phases: a case study of road infrastructure projects. International Journal of Construction Management, 21(2), 1–13

    Google Scholar 

  14. Kordestani, N., et al. (2018). A practical framework to facilitate the presence of o&m contractors in the pre-occupancy phases: a case study, in Int J project organization and management.

  15. Jadidol Eslami, S., et al. (2016). Benefits of using constructability, operability, and maintainability in infrastructure projects: a meta-synthesis, in The CRICOM 21st international conference on advancement of construction management and real state, 14–17 December 2016, The University of Hong Kong. p. 347–363.

  16. Kordestani, N., Saghatforoush, E. (2019). Necessity of integrating the maintenance stage with the early stages of projects, in 14th International OTMC-Conference, Zagreb. p. 351–362.

  17. Kordestani, N., et al. (2017). Research trends on benefits of implementing constructability, operability, and maintainability. Journal of Engineering, Project and Production Management, 7(2), 55–62

    Google Scholar 

  18. Levik, K., General, A.D. (2001). How to sell the message “road maintenance is necessary” to decision makers, in first road transportation technology transfer conference in Africa. p. 460–467.

  19. Chew, M. Y. L., Tan, S. S., & Kang, K. H. (2004). Building maintainability—review of state of the art. Journal of Architectural Engineering, 10(3), 80–87

    Google Scholar 

  20. Frame, J.D. (2003). Managing projects in organizations: how to make the best use of time, techniques, and people. John Wiley and Sons.

  21. Lai, A.W., and Pang, P. S. (2010). Measuring performance for building maintenance providers, in Journal of construction engineering and management. p. 864–876.

  22. Blanchard, B. S., & Lowery, E. E. (1995). Maintainability: principles and practices. McGraw-Hill.

    Google Scholar 

  23. Zhu, L., Shan, M., & Hwang, B.-G. (2018). Overview of design for maintainability in building and construction research. Journal of Performance of Constructed Facilities, 32(1), 04017116

    Google Scholar 

  24. Ganisen, S., et al. (2015). the identification of design for maintainability imperatives to achieve cost effective building maintenance: a delphi study. Jurnal Teknologi, 77(30), 75–88

    Google Scholar 

  25. Ismail, N. and Mohamad M.I. (2015) Factors in building design that improve building maintainability in Malaysia, in 31st Annual ARCOM Conference, Association of Researchers in Construction Management. p. 905–9014.

  26. Mayer, P., and Brewer, B. (2001). Auditing for durability. Proceedings of the whole-life performance of facades, centre for window and cladding technology. p. 23–32.

  27. Ishak, S. N. H., Chohan, A. H., & Ramly, A. (2007). Implications of design deficiency on building maintenance at post-occupational stage. Journal of Building Appraisal, 3(2), 115–124

    Google Scholar 

  28. Liu, R. and Issa, R.R.A. (2014) Design for maintenance accessibility using BIM tools. Facilities. p. 153–159.

  29. MacLeamy, P. (2004). Collaboration, integrated information and the project lifecycle in building design, construction and operation, in WP-1202, The construction users roundtable.

  30. Meng, X. (2013). Involvement of facilities management specialists in building design: UK experience. Journal of Performance of Constructed Facilities, 27(5), 500–507

    Google Scholar 

  31. Kordestani Ghalenoei, N. S. (2020). Operability and maintainability obstacles: an exploratory factor analysis approach. Int J Advanced Operations Management. in press.

    Google Scholar 

  32. Shen, Q., Lo, K.-K., & Wang, Q. (1998). Priority setting in maintenance management: a modified multi-attribute approach using analytic hierarchy process. Construction Management and Economics, 16(6), 693–702

    Google Scholar 

  33. Meier, J. R., & Russell, J. S. (2000). Model process for implementing maintainability. Journal of Construction Engineering and Management, 126(6), 440–450

    Google Scholar 

  34. May, D., S. Lavy, and Shohet I.M. (2009) Integrated healthcare facilities maintenance management model: case studies. Facilities.

  35. Bianchi, C. (2013) Implementation of road operation maintenance aspects in the planning and design phase, Department of Civil and Environmental Engineering.

  36. Flores-Colen, I., & de Brito, J. (2010). A systematic approach for maintenance budgeting of buildings façades based on predictive and preventive strategies. Construction and Building Materials, 24(9), 1718–1729

    Google Scholar 

  37. El-Haram, M. A., & Horner, M. W. (2002). Factors affecting housing maintenance cost. Journal of Quality in Maintenance Engineering, 8, 115–123

    Google Scholar 

  38. Ali, A. S., et al. (2010). Factors affecting housing maintenance cost in Malaysia. Journal of Facilities Management, 8, 285–298

    Google Scholar 

  39. Arditi, D., & Nawakorawit, M. (1999). Designing buildings for maintenance: designers’ perspective. Journal of Architectural Engineering, 5(4), 107–116

    Google Scholar 

  40. Liu, R., & Issa, R. R. A. (2016). Survey: common knowledge in BIM for facility maintenance. Journal of Performance of Constructed Facilities, 30(3), 4015033

    Google Scholar 

  41. Karim, H. (2010). Evaluation of attempts for efficient road maintenance-knowledge compilation. Balt J Road Bridge Eng, 5(4), 229–239

    Google Scholar 

  42. Hassanain, M. A., Fatayer, F., & Al-Hammad, A.-M. (2016). Design-phase maintenance checklist for electrical systems. Journal of Performance of Constructed Facilities, 30(2), 6015003

    Google Scholar 

  43. Ling, F.Y.Y. (2014) Strategies for integrating design and construction and operations and maintenance supply chains in Singapore. Structural Survey. 32:158–182.

  44. Ali, K.N., et al. (2002) Improving the business process of reactive maintenance projects. Facilities, 20: 251–261.

  45. Lai, A. W. Y., & Pang, P. S. M. (2010). Measuring performance for building maintenance providers. Journal of Construction Engineering and Management, 136(8), 864–876

    Google Scholar 

  46. Chew, M.Y.L., et al. (2008) Grading maintainability parameters for sanitary-plumbing system for high-rise residential buildings. Women’s career advancement and training and development in the, p. 887–900.

  47. Sohail, M., Cavill, S., & Cotton, A. P. (2005). Sustainable operation and maintenance of urban infrastructure: Myth or reality? Journal of Urban Planning and Development, 131(1), 39–49

    Google Scholar 

  48. Bucarelli, N., J. Zhang, and C. Wang (2018). Maintainability assessment of light design using game simulation, virtual reality, and brain sensing technologies. in Construction Research Congress 2018: Construction Information Technology–Selected Papers from the Construction Research Congress 2018.

  49. Khalek, I. A., Chalhoub, J., & Ayer, S. K. (2019). Indicators of effective design for maintainability in conceptual design. AEI, 2, 309–315

    Google Scholar 

  50. Carpenter, T., & Ollmann, A. (2008). Sustainable design and development: an integrated team. Construction Account and Taxation.

    Google Scholar 

  51. Hassanain, M. A., Fatayer, F., & Al-Hammad, A.-M. (2015). Design phase maintenance checklist for water supply and drainage systems. Journal of Performance of Constructed Facilities, 29(3), 04014082

    Google Scholar 

  52. De Silva, N., et al. (2004). Improving the maintainability of buildings in Singapore. Building and Environment, 39(10), 1243–1251

    Google Scholar 

  53. Nichols, M. (2007). Review of highways agency’s major roads programme. Springer.

    Google Scholar 

  54. Ilozor, B. D., Okoroh, M. I., & Egbu, C. E. (2004). Understanding residential house defects in Australia from the State of Victoria. Building and Environment, 39(3), 327–337

    Google Scholar 

  55. Adejimi, A. (2005). Poor building maintenance in Nigeria: are architects free from blames, in being paper presented at the ENHIR international conference on “housing: new challenges and innovations in tomorrow’s cities” in Iceland.

  56. Shen, L., Wang, Y., & Teng, W. (2017). The moderating effect of interdependence on contracts in achieving equity versus efficiency in interfirm relationships. Journal of Business Research, 78, 277–284

    Google Scholar 

  57. Kosko, B. (1986). Fuzzy cognitive maps. International Journal of Man-Machine Studies, 24(1), 65–75

    MATH  Google Scholar 

  58. Salmeron, J. L., & Froelich, W. (2016). Dynamic optimization of fuzzy cognitive maps for time series forecasting. Knowledge-Based Systems, 105, 29–37

    Google Scholar 

  59. Salmeron, J. L., et al. (2019). Learning fuzzy cognitive maps with modified asexual reproduction optimisation algorithm. Knowledge-Based Systems, 163, 723–735

    Google Scholar 

  60. Papageorgiou, E. I. (2010). A novel approach on constructed dynamic fuzzy cognitive maps using fuzzified decision trees and knowledge-extraction techniques. (pp. 43–70). Fuzzy Cognitive Maps.

    Google Scholar 

  61. Groumpos, P. P. (2010). Fuzzy cognitive maps: basic theories and their application to complex systems. (pp. 1–22). Springer.

    Google Scholar 

  62. Glaser, B. (1978). Theoretical sensitivity. Advances in the methodology of grounded theory.

    Google Scholar 

  63. Rodriguez-Repiso, L., Setchi, R., & Salmeron, J. L. (2007). Modelling IT projects success: emerging methodologies reviewed. Technovation, 27(10), 582–594

    Google Scholar 

  64. Yaman, D., & Polat, S. (2009). A fuzzy cognitive map approach for effect-based operations: an illustrative case. Information Sciences, 179(4), 382–403

    Google Scholar 

  65. Zare Ravasan, A., & Mansouri, T. (2014). FCM-based dynamic modeling of ERP implementation critical failure factors. International Journal of Enterprise Information Systems (IJEIS), 10(1), 32–52

    Google Scholar 

  66. Papageorgiou, E. I., Markinos, A., & Gemptos, T. (2009). Application of fuzzy cognitive maps for cotton yield management in precision farming. Expert Systems with Applications, 36(10), 12399–12413

    Google Scholar 

  67. Lopez, C., & Salmeron, J. L. (2014). Dynamic risks modelling in ERP maintenance projects with FCM. Information Sciences, 256, 25–45

    Google Scholar 

  68. Salmeron, J. L. (2010). Modelling grey uncertainty with Fuzzy Grey cognitive maps. Expert Systems with Applications, 37(12), 7581–7588

    Google Scholar 

  69. Salmeron, J. L. (2009). Augmented fuzzy cognitive maps for modelling LMS critical success factors. Know-Based Syst, 22(4), 275–278

    MathSciNet  Google Scholar 

  70. Saghatforoush, E. (2014). Extension of constructability to include operation and maintenance for infrastructure projects. Queensland University of Technology.

    Google Scholar 

  71. Stach, W., Kurgan, L., & Pedrycz, W. (2010). Expert-based and computational methods for developing fuzzy cognitive maps fuzzy cognitive maps. (pp. 23–41). Springer.

    MATH  Google Scholar 

  72. Zare Ravasan, A., & Mansouri, T. (2016). A dynamic ERP critical failure factors modelling with FCM throughout project lifecycle phases. Production Planning and Control, 27(2), 65–82

    Google Scholar 

  73. Assaf, S., Al-Hammad, A.-M., & Al-Shihah, M. (1996). Effects of faulty design and construction on building maintenance. Journal of Performance of Constructed Facilities, 10(4), 171–174

    Google Scholar 

  74. Al-Zubaidi, H. (1997). Assessing the demand for building maintenance in a major hospital complex. Property Management, 1, 97–123

    Google Scholar 

  75. Lovallo, D., and Kahneman, D. (2003) Delusions of success, in Harvard business review. p. 56–63.

  76. Omonyo, A. B. (2018). Influence of human behaviour on success of complex public Infrastructural megaprojects in Kenya. Orsea Journal, 7(1), 8

    Google Scholar 

  77. Pishdad-Bozorgi, P. Y. J. (2016). Symbiotic relationships between integrated project delivery (IPD) and trust. International Journal of Construction education and Research, 12(3), 179–192

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ehsan Saghatforoush.

Appendix

Appendix

See (Table

Table 8 The effects among O&M barriers and their effects

8).

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Kordestani Ghaleenoei, N., Saghatforoush, E., Mansouri, T. et al. An FCM-based Dynamic Modeling of Operability and Maintainability Barriers in Road Projects. Int. J. Pavement Res. Technol. 15, 367–383 (2022). https://doi.org/10.1007/s42947-021-00027-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42947-021-00027-z

Keywords

  • Fuzzy cognitive mapping (FCM)
  • Operability and maintainability (OM)
  • Operability and maintainability barriers
  • Road infrastructure