ارزیابی کارایی و تحلیل توان مدیریتی بخش انتقال برق منطقه ای با حضور متغیرهای زمینه ای

صنعت برق یکی از صنایع مهم و اساسی در جهت رشد و توسعه اقتصادی کشور به شمار می آید. از این رو ارزیابی عملکرد این صنعت و شناخت نقاط قوت و ضعف هر یک از بخش های آن اعم از بخش تولید، انتقال و توزیع می تواند موجب بهبود رشد اقتصادی در زمینه های مختلف شود. با توجه به اهمیت بخش انتقال، در مطالعه حاضر عملکرد 16 شرکت برق منطقه ای ایران طی سال های 1390 تا 1398 با توجه به اثر متغیرهای زمینه ای بر کارایی مورد تحلیل و ارزیابی قرار می گیرد. در این راستا از دو تکنیک تحلیل پوششی داده ها و حداقل مربعات معمولی به ترتیب جهت تعیین امتیاز کارایی و تخمین اثر متغیرهای زمینه ای بر کارایی استفاده می شود. به این منظور در مرحله نخست، کارایی تکنیکی هر یک از شرکت ها با توجه به ورودی ها و خروجی های مختص آن ها بر اساس تکنیک تحلیل پوششی داده ها محاسبه می شود. در مرحله دوم لگاریتم مقدار کارایی به دست آمده بر روی متغیرهای زمینه ای رگرسیون می شود تا میزان اثر آن ها بر کارایی تعیین گردد. باقی مانده حاصل از رگرسیون صورت گرفته تحت عنوان توان مدیریتی معرفی می شود. در پایان با توجه به کارایی اصلاح شده پس از حذف اثر متغیرهای زمینه ای معیاری برای رتبه بندی شرکت‌ها ارائه می شود.

efficiency assessment and managerial ability analysis of the regional electricity transmission sector with the presence of contextual variables

the electricity industry plays a pivotal role in a country’s economic growth and development. therefore, it is imperative to assess its performance and identify the strengths and weaknesses of its different sectors, such as production, transmission, and distribution, to enhance economic growth in diverse areas. given the significance of the transmission sector, this research focuses on analyzing and evaluating the performance of 16 regional electricity companies in iran from 1390 to 1398, with the aim of comprehending the impact of contextual variables on efficiency. to achieve this, the study will utilize two techniques - data envelopment analysis (dea) and ordinary least squares (ols) - to determine the efficiency score and estimate the effect of contextual variables on efficiency, respectively. in the first stage, the dea technique is employed to calculate the technical efficiency of each company, considering their specific inputs and outputs. in the second stage, the logarithm of the efficiency scores obtained is regressed on contextual variables to establish their effect on efficiency. the residual derived from the regression is referred to as managerial ability. finally, the companies are ranked based on their modified efficiency after removing the impact of contextual variables.introduction the electricity industry comprises three key sectors: production, transmission, and distribution. it stands as one of the most crucial economic infrastructures in the country, exerting significant influence on industrial, agricultural, service, and other sectors. undoubtedly, the growth of the electricity industry drives the nation’s economic development and progress, contributing to the prosperity and comfort of its citizens (tavassoli et al., 2020). consequently, analyzing and examining the growth trajectory of each sector across different years becomes pivotal in mitigating adverse effects and fostering progress within this domain.in recent years, numerous researchers have conducted studies in this field. some have independently evaluated each production, transmission, and distribution sector, while others have adopted a comprehensive approach by considering the integrated three-stage network structure. the research background highlights that the transmission sector has received less attention from researchers than other sectors. this is noteworthy because, following electricity production, the transmission process and energy accessibility to consumers are paramount. the absence of proper energy transfer can result in consumer dissatisfaction, financial losses, and stagnation within the competitive economic market. therefore, identifying the strengths and weaknesses of the transmission sector’s performance and comparing regional electricity transmission companies can effectively help enhance the performance level of each.one technique that has captured researchers’ attention for evaluating the electricity industry’s performance is the data envelopment analysis (dea) technique. dea is a non-parametric method used to assess the performance of homogeneous units, considering multiple inputs and outputs. it was initially introduced in 1978 by charnes et al. the initial model was built upon the assumption of constant returns to scale. subsequently, banker et al. (1984) extended it by presenting a model under the assumption of returns to a variable scale.importantly, traditional dea models evaluate a system’s performance based on specific inputs and outputs consumed and produced by the unit. however, various factors, such as contextual variables, managerial ability, and skill, can significantly influence performance and productivity. a crucial point to consider is that managerial abilities are not always overtly visible. this lack of direct visibility can impede accurate measurement.