Research Article

Value Efficiency in Centralized Resource Allocation with Missing Data: A Case Study of Construction Projects

Authors

  • Ali Sedaghatpour * Department of Industrial Management, Kish International Branch, Islamic Azad University, Kish, Iran.
  • Morteza Shafiee Department of Industrial Management, Shiraz Branch, Islamic Azad University, Shiraz, Iran.
  • Hassan Soltani Department of Industrial Management, Shiraz Branch, Islamic Azad University, Shiraz, Iran.
  • Mohammad Reza Mozaffari Department of Mathematics, Shiraz Branch, Islamic Azad University, Shiraz, Iran.

https://doi.org/10.22105/raise.v2i4.92

Abstract

This study proposes a mathematical model for evaluating the performance of construction projects based on the Value Efficiency (EV) approach under conditions of missing data. The proposed framework integrates Data Envelopment Analysis (DEA) with missing data estimation techniques to assess the relative efficiency of Decision-Making Units (DMUs) in real-world environments characterized by incomplete information. To address missing values in undesirable outputs, two replacement strategies are employed: mean substitution and an efficiency-based scenario approach. The empirical application includes 33 construction projects affiliated with Sadra New Town Development Company in Shiraz (before 2024). The results demonstrate that the proposed model effectively distinguishes between efficient and inefficient projects and provides a scientific basis for improving Centralized Resource Allocation (CRA) decisions.

Keywords

Value efficiency Data envelopment analysis Missing data Centralized resource allocation Construction projects
References (17)
  1. [1] Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429-444. https://doi.org/10.1016/0377-2217(78)90138-8

  2. [2] Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management science, 30(9), 1078-1092. https://doi.org/10.1287/mnsc.30.9.1078

  3. [3] Cook, W. D., & Seiford, L. M. (2009). Data envelopment analysis (DEA)–Thirty years on. European journal of operational research, 192(1), 1-17. https://doi.org/10.1016/j.ejor.2008.01.032

  4. [4] Mergoni, A., Emrouznejad, A., & De Witte, K. (2025). Fifty years of data envelopment analysis. European journal of operational research, 326(3), 389-412. https://doi.org/10.1016/j.ejor.2024.12.049

  5. [5] Banihashemi, S. A., & Khalilzadeh, M. (2021). Time-cost-quality-environmental impact trade-off resource-constrained project scheduling problem with DEA approach. Engineering, construction and architectural management, 28(7), 1979-2004. https://doi.org/10.1108/ECAM-05-2020-0350

Article Metrics

How to Cite

Sedaghatpour, A. ., Shafiee, M. ., Soltani, H. ., & Mozaffari, M. R. . (2025). Value Efficiency in Centralized Resource Allocation with Missing Data: A Case Study of Construction Projects. Research Annals of Industrial and Systems Engineering, 2(4), 238-248. https://doi.org/10.22105/raise.v2i4.92

Similar Articles

1-10 of 65

You may also start an advanced similarity search for this article.