International Journal of Mathematical, Engineering and Management Sciences

ISSN: 2455-7749

Assigning Weights for Modified Project Quarter Back Rating Based Construction Project Performance Model

Prachi Vinod Ingle
Department of Civil Engineering, National Institute of Technology Karnataka, Surathkal, India.

Gangadhar Mahesh
Department of Civil Engineering, National Institute of Technology Karnataka, Surathkal, India.

DOI https://dx.doi.org/10.33889/IJMEMS.2019.4.4-071

Received on February 18, 2019
  ;
Accepted on April 22, 2019

Abstract

The Indian construction industry is facing challenges due to performance shortfalls. The construction projects are highly complex, distinctive, fragmented and do not have of well-established performance assessment models to evaluate their project success. Assessing overall project success is not possible to measure by single factor. To address this limitation, the Modified Project Quarter Back Rating (PQR) model was developed for the Indian construction industry. Modified PQR model’s output is a project score based on performance areas affecting project success and outcome. The model integrates ten performance areas that have identified through literature review. Performance areas included in the model are; (i) Cost (ii) Schedule (iii) Stakeholder satisfaction (iv) Safety (v) Quality (vi) Finance (vii) Environment (viii) Communication and collaboration (ix) Customer relation and (x) Productivity. These performance areas are measured through different performance metrics; i.e. performance metrics scores are aggregated to compute performance area scores. The model gives a single score that will help in comparing overall performance for different projects. This paper attempted to highlight the importance of performance metrics in modified Project Quarter Back Rating (PQR) based construction project performance assessment model for the Indian construction industry. The validity of the model needs assigning appropriate weights to the performance metrics as the weightage determines the relevance. Appropriate weights were determined using two round Delphi survey with 12 experts. Findings reveal that two performance metrics; return business from customer relation and OSHA recordable from safety have high weights. This modified PQR model will help key participants of the industry to compare the performance of various projects and to monitor performance areas that impact project performance rating.

Keywords- Project performance, Project success, Project scores, Modified PQR model, Delphi technique.

Citation

Ingle, P. V., & Mahesh, G. (2019). Assigning Weights for Modified Project Quarter Back Rating Based Construction Project Performance Model. International Journal of Mathematical, Engineering and Management Sciences, 4(4), 895-904. https://dx.doi.org/10.33889/IJMEMS.2019.4.4-071.

Conflict of Interest

The authors confirm that there is no conflict of interest to declare for this publication.

Acknowledgements

The authors acknowledge and express the gratitude to the reviewer’s constructive comments and valuable suggestion towards the improvement of the paper.

References

Bourne, M., Mills, J., Wilcox, M., Neely, A., & Platts, K. (2000). Designing, implementing and updating performance measurement systems. International Journal of Operations & Production Management, 20(7), 754-771.

Cicmil, S., & Hodgson, D. (2006). New possibilities for project management theory: A critical engagement. Project Management Journal, 37(3), 111-122.

Dawood, N., & Sikka, S. (2009). Development of 4D based performance indicators in construction industry. Engineering, Construction and Architectural Management, 16(5), 438-458.

El Asmar, M., Hanna, A.S., & Loh, W.Y. (2015). Evaluating integrated project delivery using the project quarterback rating. Journal of Construction Engineering and Management, 142(1), 04015046.

Hair, J.F., Anderson, R.E., Babin, B.J., & Black, W.C. (2010). Multivariate data analysis: a global perspective (Vol. 7). Pearson, Upper Saddle River, NJ

Hallowell, M.R., & Gambatese, J.A. (2009). Activity-based safety risk quantification for concrete formwork construction. Journal of Construction Engineering and Management, 135(10), 990-998.

Hanna, A.S., Lotfallah, W., Aoun, D.G., & Asmar, M.E. (2014). Mathematical formulation of the project quarterback rating: New framework to assess construction project performance. Journal of Construction Engineering and Management, 140(8), 04014033.

Hatzichristos, T., & Giaoutzi, M. (2006). Landfill siting using GIS, fuzzy logic and the Delphi method. International Journal of Environmental Technology and Management, 6(1), 218-231.

Heras Saizarbitoria, I. (2006). How quality management models influence company results–conclusions of an empirical study based on the Delphi method. Total Quality Management & Business Excellence, 17(6), 775-794

Jugdev, K., & Müller, R. (2005). A retrospective look at our evolving understanding of project success. Project management journal, 36(4), 19-31.

Ke, Y., Wang, S., Chan, A.P., & Lam, P.T. (2010). Preferred risk allocation in China’s public–private partnership (PPP) projects. International Journal of Project Management, 28(5), 482-492.

Lin, L.K., Chang, C.C., & Lin, Y.C. (2011). Structure development and performance evaluation of construction knowledge management system. Journal of Civil Engineering and Management, 17(2), 184-196.

Liu, J., Love, P.E., Davis, P.R., Smith, J., & Regan, M. (2014). Conceptual framework for the performance measurement of public-private partnerships. Journal of Infrastructure Systems, 21(1), 04014023.

Nijkamp, P., Rietveld, P., & Voogd, H. (1990). Multicriteria evaluation in physical planning, North-Holland, Amsterdam.

Papic, L., Mladjenovic, M., Carrión García, A., & Aggrawal, D. (2017). Significant factors of the successful lean six-sigma implementation. International Journal of Mathematical, Engineering and Management Sciences, 2(2), 85-109.

Papke-Shields, K.E., Beise, C., & Quan, J. (2010). Do project managers practice what they preach, and does it matter to project success?. International Journal of Project Management, 28(7), 650-662.

Perera, B.A.K.S., Rameezdeen, R., Chileshe, N., & Hosseini, M.R. (2014). Enhancing the effectiveness of risk management practices in Sri Lankan road construction projects: A Delphi approach. International Journal of Construction Management, 14(1), 1-14.

Scholl, W., König, C., Meyer, B., & Heisig, P. (2004). The future of knowledge management: an international Delphi study. Journal of Knowledge Management, 8(2), 19-35.

Shapira, A., & Lyachin, B. (2009). Identification and analysis of factors affecting safety on construction sites with tower cranes. Journal of Construction Engineering and Management, 135(1), 24-33.

Shenhar, A.J., Dvir, D., Levy, O., & Maltz, A.C. (2001). Project success: a multidimensional strategic concept. Long Range Planning, 34(6), 699-725.

Singh, S., & Singh, L.P. (2017) Occupational safety culture of workers at shop floor in medium scale iron and steel industries of Punjab state in India: development of safety index. Journal of Steel Structures & Construction, 3(126), 1000126.

Skulmoski, G.J., Hartman, F.T., & Krahn, J. (2007). The Delphi method for graduate research. Journal of Information Technology Education: Research, 6(1), 1-21.

Yong, Y.C., & Mustaffa, N.E. (2013). Critical success factors for Malaysian construction projects: an empirical assessment. Construction Management and Economics, 31(9), 959-978.

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