Volume 32, Issue 1 (IJIEPR 2021)                   IJIEPR 2021, 32(1): 47-64 | Back to browse issues page

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Nedaei H, Jalali Naini S G, Makui A. A DEA approach to measure teammate-adjusted efficiencies incorporating learning expectations: An application to oil & gas wells drilling. IJIEPR. 2021; 32 (1) :47-64
URL: http://ijiepr.iust.ac.ir/article-1-1039-en.html
1- Department of Industrial Engineering, Iran University of Science and Technology
2- Department of Industrial Engineering, Iran University of Science and Technology , sgjalali@iust.ac.ir
Abstract:   (251 Views)
Data envelopment analysis (DEA) measures the relative efficiency of decision-making units (DMU) with multiple inputs and multiple outputs. In the case of considering a working team as a DMU, it often comprises multiple positions with several employees. However, there is no method to measure the efficiency of employees individually taking account the effect of teammates. This paper presents a model to measure the efficiency of employees in a way that they are fairly evaluated regarding their teammates’ relative performances. Moreover, the learning expectations and the effect of learning lost due to operation breaks are incorporated into the DEA model. This model is thus able to rank the employees working in each position that can then be utilized within award systems. The capabilities of the proposed model are then explored by a case study of 20 wells with 160 distinct operations in the South Pars gas field, which is the first application of DEA in the oil and gas wells drilling performance analysis.
 
Full-Text [PDF 304 kb]   (112 Downloads)    
Type of Study: Research | Subject: Productivity Improvement
Received: 2020/03/28 | Accepted: 2020/09/21 | Published: 2020/12/11

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