ANALYSIS ON PROJECT PORTFOLIO MANAGEMENT PRACTICES IN INDIAN CONSTRUCTION INDUSTRY

Authors

  • Sivasundara Vinayagam National Institute of Construction Management And Research (NICMAR), Hyderabad, India.
  • Hemprashant R V National Institute of Construction Management And Research (NICMAR), Hyderabad, India.
  • Sruthy S National Institute of Construction Management And Research (NICMAR), Hyderabad, India.
  • Vidya Sanjeev National Institute of Construction Management And Research (NICMAR), Hyderabad, India.
  • Dr P Muralidhar National Institute of Construction management And Research (NICMAR), Hyderabad, India

DOI:

https://doi.org/10.33736/jcest.3982.2021

Keywords:

Project Portfolio management (PPM), construction industry, managing projects, multi criteria decision making (MCDM) techniques, entropy method, simple additive weighting (SAW) method, combinative distance based assessment (CODAS) method

Abstract

Project Portfolio management (PPM) is a combination of projects under the sponsorship of a particular construction organization sharing the scarce resources, managing projects and programs within the portfolio. It requires different strategies, models and practices. Many organizations across the country have projects in their sector in different places. However they abandoned temporarily suspended or closed within a decade which is troublesome. Proper PPM helps to execute the construction project effectively. As such, the aim of this research paper is to identify PPM practices in different construction organizations with a view to examine the effects of such practices on the project portfolio. The current research topic focuses on analysing the project performance of different construction projects using Project Portfolio Management practices. In this research a questionnaire survey related to the Project Portfolio Management on four major practices is carried out among the various professionals in Indian Construction Industry with help of Multi Criteria Decision Making (MCDM) techniques such as Entropy Method, SAW, CODAS methods and ranking the various project portfolio.

References

Madic, B., Trujic, V. and Mihajlovic, I. (2011). Project portfolio management implementation review. African J. Bus. Management, 5(2), 240-248.

Oostuizen, C., Grobbelaar, S. S. and Bam, W. G. (2018). Project Portfolio Management Best Practice and Implementation: A South African Perspective. Int. J. Innovative. Technology. Management, 15(4).

https://doi.org/10.1142/S0219877018500360

Barbosa, M. W., & de Ávila Rodrigues, C. (2020). Project Portfolio Management teaching: Contributions of a gamified approach. The International Journal of Management Education, 18(2), 100388.

https://doi.org/10.1016/j.ijme.2020.100388

Hoffmann, D., Ahlemann, F., & Reining, S. (2020). Reconciling alignment, efficiency, and agility in IT project portfolio management: Recommendations based on a revelatory case study. International journal of project management, 38(2), 124-136.

https://doi.org/10.1016/j.ijproman.2020.01.004

Micán, C., Fernandes, A. G. G., & Araújo, M. M. T. D. (2020). Project portfolio risk management: a structured literature review with future directions for research. International Journal of information systems and project management, 8(3), 67-84.

Okechukwu, E. U., & Egbo, D. E. (2017). Effect of Project Portfolio Management on the Performance of Business Organizations in Enugu Nigeria. International Journal of Academic Research in Business and Social Sciences, 7(9), 591-604.

Auti, A., & Skitmore, M. (2008). Construction project management in India. International Journal of Construction Management, 8(2), 65-77.

https://doi.org/10.1080/15623599.2008.10773116

Ko, J. H., & Kim, D. (2019). The effects of maturity of project portfolio management and business alignment on PMO efficiency. Sustainability, 11(1), 238.

https://doi.org/10.3390/su11010238

Mahmoudi, A., Javed, S. A., Liu, S., & Deng, X. (2020). Distinguishing coefficient driven sensitivity analysis of GRA model for intelligent decisions: application in project management. Technological and Economic Development of Economy, 26(3), 621-641.

https://doi.org/10.3846/tede.2020.11890

Pan, Y., Liu, S., Zhou, Y., & Song, G. (2020). Regression Analysis for Outcome-Dependent Sampling Design under the Covariate-Adjusted Additive Hazards Model. Complexity, 1 - 13.

https://doi.org/10.1155/2020/2790123

Li, J., Song, Y., & Cai, Y. (2020). Focus topics on micro plastics in soil: analytical methods, Occurrence, transport, and ecological risks. Environmental Pollution, 257, 113570.

https://doi.org/10.1016/j.envpol.2019.113570

Sałabun, W., Wątróbski, J., & Shekhovtsov, A. (2020). Are mcda methods benchmark able? a comparative study of topsis, vikor, copras, and promethee ii methods. Symmetry, 12(9), 1549.

https://doi.org/10.3390/sym12091549

Seker, S. (2020). A novel interval-valued intuitionistic trapezoidal fuzzy combinative distance-based assessment (CODAS) method. Soft Computing, 24(3), 2287-2300.

https://doi.org/10.1007/s00500-019-04059-3

Badi, I., & Pamucar, D. (2020). Supplier selection for Steelmaking Company by using combined Grey-MARCOS methods. Decision Making: Applications in Management and Engineering, 3(2), 37-48.

https://doi.org/10.31181/dmame2003037b

Karaşan, A., Boltürk, E., & Gündoğdu, F. K. (2021). Assessment of livability indices of suburban places of istanbul by using spherical fuzzy CODAS method. In: Kahraman C., Kutlu Gündoğdu F. (eds) Decision Making with Spherical Fuzzy Sets. Studies in Fuzziness and Soft Computing, vol 392, 277-293, Springer, Cham.

https://doi.org/10.1007/978-3-030-45461-6_12

Bolturk, E., & Kahraman, C. (2018). Interval-valued intuitionistic fuzzy CODAS method and its application to wave energy facility location selection problem. Journal of Intelligent & Fuzzy Systems, 35(4), 4865-4877.

https://doi.org/10.3233/JIFS-18979

Peng, X., & Ma, X. (2020). Pythagorean fuzzy multi-criteria decision making method based on CODAS with new score function. Journal of Intelligent & Fuzzy Systems, 38(3), 3307-3318.

https://doi.org/10.3233/JIFS-190043

Rani, P., Mishra, A. R., Rezaei, G., Liao, H., & Mardani, A. (2020). Extended Pythagorean fuzzy TOPSIS method based on similarity measure for sustainable recycling partner selection. International Journal of Fuzzy Systems, 22(2), 735-747.

https://doi.org/10.1007/s40815-019-00689-9

Tüysüz, N., & Kahraman, C. (2020). CODAS method using Z-fuzzy numbers. Journal of Intelligent & Fuzzy Systems, 38(2), 1649-1662

https://doi.org/10.3233/JIFS-182733

Wang, Z., Parhi, S. S., Rangaiah, G. P., & Jana, A. K. (2020). Analysis of Weighting and Selection Methods for Pareto-Optimal Solutions of Multi objective Optimization in Chemical Engineering Applications. Industrial & Engineering Chemistry Research, 59(33), 14850-14867.

https://doi.org/10.1021/acs.iecr.0c00969

Downloads

Published

2021-09-30

How to Cite

Vinayagam, S., R V, H. . . ., S, S. ., Sanjeev, V., & Muralidhar, P. . (2021). ANALYSIS ON PROJECT PORTFOLIO MANAGEMENT PRACTICES IN INDIAN CONSTRUCTION INDUSTRY. Journal of Civil Engineering, Science and Technology, 12(2), 179–188. https://doi.org/10.33736/jcest.3982.2021