دانشگاه علامه طباطبائی پژوهش‌های اقتصادی ایران 1726-0728 30 104 2025 09 23 A Ranking of Iranian Provinces and Counties by Value-Added Shares in 18 Subsectors of ISIC Rev. 4 Using VIKOR and Shannon Entropy رتبه‌بندی شهرستان‌ها و استان‌های کشور براساس سهم ارزش افزوده در زیربخش‌های 18گانه ISIC 4.0 با روش VIKOR و وزن‌دهی آنتروپی Shanon 234 276 20615 10.22054/ijer.2026.85701.1358 FA مرتضی قنبرزاده چالشتری دانشجوی دکتری رشته اقتصاد بخش عمومی، دانشگاه اصفهان، اصفهان، ایران پارسا ریاحی دهکردی کارشناسی ارشد مدیریت استراتژیک، شرکت ریل پرداز نوآفرین، تهران، ایران Journal Article 2025 05 06 Economics examines the optimal allocation of scarce resources in the face of unlimited demands. This requires access to reliable and relevant information to support effective prioritization. In the development literature, particular emphasis is placed on the capacity and relative position of regions within the national production system, as these factors constitute pillars of balanced development. The present study aimed to rank Iranian provinces and counties based on their shares in value added. Adopting a descriptive–analytical approach, the research selected the statistical population comprising 457 counties of the country for the period 2017–2020 (corresponding to 1396–1399 in the solar Hijri calendar). Given the comprehensive scope of the study, no sampling was undertaken, and the analysis was conducted using a census method. The VIKOR multi-criteria decision-making technique was applied, and Shannon entropy was employed to determine criterion weights. The input variable was each county’s share of value added relative to the national total in the corresponding sector. The data was obtained from statistical tables (published by the Statistical Center of Iran) and regional accounts. The results indicated that Tehran, Rey, and Mashhad counties achieved the highest rankings in both years, whereas Margoun, Karkheh, and Angut ranked the lowest. Provinces were also ranked using both direct and indirect approaches. Under the direct method, Tehran, Khuzestan, and Bushehr ranked highest, while Ilam, Chaharmahal-and-Bakhtiari, and North Khorasan were positioned at the lower end of the ranking. In the indirect method, Qom, Tehran, and Bushehr occupied the top positions, whereas Chaharmahal-and-Bakhtiari, South Khorasan, and Sistan-and-Baluchestan ranked lowest. Overall, the findings revealed a significant concentration of production in a limited number of regions, highlighting the necessity of targeted regional policies to promote balanced development. The results can provide valuable guidance for policymakers in designing resource allocation strategies and regional economic planning initiatives. Introduction Under current national economic conditions, there is broad consensus—particularly among economists, experts, and policymakers—that Iran’s level of economic growth and production does not align with the capacity of its human and natural resources. A substantial portion of economic potential remains underutilized, leading to high unemployment of resources—especially labor—and an excessive reliance of national economic growth on oil revenues, which are inherently volatile. This dependence has contributed to instability in economic planning and key macroeconomic variables. These factors have reduced overall productivity in the national economy, thus highlighting an urgent need for structural reforms aimed at the more efficient utilization of economic resources and potential. An examination of Iran’s regional economy reveals significant disparities in performance, with some regions achieving higher-than-average levels of economic growth. Owing to differences in regional potential, levels of development across provinces are uneven in the industrial, agricultural, and service sectors. Failure to adequately recognize and utilize regional capacities leads to misaligned investments and the persistence of underdevelopment, despite the implementation of numerous national and regional development programs. These programs have largely been unable to reduce economic, social, and spatial inequalities. As a result, severe poverty in certain regions, unequal employment opportunities, uneven access to facilities, and migration continue to pose major development challenges. Identifying the factors that influence regional economic growth enables more informed policymaking at both the national and local levels. In light of the long-term objectives set out in the Twenty-Year Vision Document—particularly the goal of attaining a leading economic position in the region—continuous monitoring of economic indicators is essential. One of the most important indicators in this regard is sectoral value added at the provincial level. However, the absence of county-level accounts represents a significant informational gap. The current study sought to address this gap by ranking provinces and counties according to their shares of value added across different economic sectors, using constant prices to eliminate the effects of inflation. The study tried to answer the following research questions: How does each province and county in Iran rank in terms of their share of value added across different economic sectors? And what is the difference between a province’s direct ranking and its indirect ranking (calculated based on the average rank of its counties)? Materials and Methods As a quantitative research based a descriptive–analytical approach, the present study relied on library-based documentary analysis and field survey data. Value-added indicators for 18 economic subsectors, classified according to ISIC Rev.4, were calculated at the county level. They were weighted using Shannon entropy, and ranked using the VIKOR method. The data was sourced from official national, provincial, and county-level accounts published by the Statistical Center of Iran, ensuring full consistency across spatial levels. The VIKOR method, grounded in multi-criteria optimization, was chosen for its ability to rank alternatives under conflicting criteria based on their proximity to the ideal solution. Results and Discussion Table 1. Comparison of Direct and Indirect Rankings of Provinces in 2019 No. Province Direct rank Indirect rank Rank difference 1 East Azerbaijan 7 16 −9 2 West Azerbaijan 9 11 −2 3 Ardabil 25 25 0 4 Isfahan 4 9 −5 5 Alborz 14 6 8 6 Ilam 29 29 0 7 Bushehr 3 3 0 8 Tehran 1 2 −1 9 Chaharmahal and Bakhtiari 30 28 2 10 South Khorasan 28 30 −2 11 Razavi Khorasan 5 24 −19 12 North Khorasan 31 26 5 13 Khuzestan 2 5 −3 14 Zanjan 26 15 11 15 Semnan 27 17 10 16 Sistan and Baluchestan 16 31 −15 17 Fars 6 19 −13 18 Qazvin 12 4 8 19 Qom 22 1 21 20 Kurdistan 23 13 10 21 Kerman 10 21 −11 22 Kohgiluyeh and Boyer-Ahmad 15 23 −8 23 Kermanshah 24 27 −3 24 Golestan 20 20 0 25 Gilan 11 12 −1 26 Lorestan 21 14 7 27 Mazandaran 8 7 1 28 Markazi 17 18 −1 29 Hormozgan 13 22 −9 30 Hamedan 19 10 9 31 Yazd 18 8 10 Source: Results Research By utilizing newly released county accounts (published in 2021) and analyzing 457 counties over multiple years, this study addressed a significant gap in subprovincial economic analysis in Iran. The results indicated that from 2017 to 2020, the counties of Tehran, Rey, and Mashhad consistently ranked first to third nationwide. In 2020, their VIKOR index values were 0, 0.8817, and 0.8877, respectively, reflecting a strong proximity to the ideal solution. In contrast, Margun (Kohgiluyeh and Boyer-Ahmad Province), Karkheh (Khuzestan Province), and Angut (Ardabil Province) were ranked the lowest, with VIKOR values approaching one. A notable finding is the pronounced spatial concentration of value added. Among the top 25 ranking positions during the period, 16 were occupied by counties in Tehran Province, underscoring the heavy concentration of economic activity in the capital region. Furthermore, Pearson correlation coefficients between the VIKOR index and population or land area were relatively weak. The strongest correlation (–0.152) was observed with urban population, which exerted roughly twice the influence of rural population. Figure 1. Map of Indirect Ranking of Provinces in 2010   Figure 2. Map of Direct Ranking of Provinces Using the VIKOR Method in 2010     Source: Results Research Sectoral analysis showed that in 2020, more than half of the national value added was generated by mining, real estate, industry, and wholesale and retail trade. Tehran County alone contributed over 16 percent of the national value added and dominated knowledge-intensive services, including information and communication, financial and insurance activities, and professional and scientific services. This structure differs markedly from the national pattern, reflecting the concentration of financial and technological infrastructure in the capital. Conclusion Iran’s development policies are largely centralized, resulting in unequal wealth distribution, rural-to-urban migration, rising unemployment, and the decline of local economic activities. The growing gap between major metropolitan areas—such as Tehran, Isfahan, Mashhad, and Shiraz—and other provincial centers highlights the urgent need for place-based regional policies tailored to local economic structures and capacities to promote more balanced and sustainable development. اقتصاد دانشی است که به تخصیص بهینه منابع محدود در برابر خواسته‌های نامحدود می‌پردازد و برای این هدف، دستیابی به اطلاعات مناسب جهت اولویت‌بندی ضروری است. در ادبیات توسعه، توجه به ظرفیت و جایگاه مناطق در نظام تولید، از ارکان مهم توسعه متوازن محسوب می‌شود. این پژوهش با هدف رتبه‌بندی شهرستان‌های کشور براساس سهم آن‌ها در ایجاد ارزش افزوده، انجام شد. روش تحقیق توصیفی-تحلیلی بوده و جامعه آماری شامل ۴۵۷ شهرستان کشور در سال‌های ۱۳۹۶ و ۱۳۹۹ بود. نمونه‌گیری انجام نشد و داده‌ها به‌صورت سرشماری بررسی شدند. از روش تصمیم‌گیری ویکور، آنتروپی شانون برای وزن‌دهی و سهم ارزش افزوده به قیمت ثابت هر بخش شهرستان از مشابه آن در کل کشور به‌عنوان ورودی استفاده شد. منبع جمع‌آوری داده‌ها، جدول‌های آماری مرکز آمار ایران و نتایج حساب‌های منطقه‌ای و شهرستانی بود. یافته‌ها نشان داد که شهرستان‌های تهران، ری و مشهد در هر دو سال در رتبه‌های برتر و شهرستان‌های مارگون، کرخه و انگوت در رتبه‌های انتهایی قرار گرفتند. همچنین، رتبه‌بندی استان‌ها به‌صورت مستقیم و غیرمستقیم صورت گرفت که در روش مستقیم، استان‌های تهران، خوزستان و بوشهر در صدر و استان‌های ایلام، چهارمحال و بختیاری و خراسان شمالی در انتها قرار گرفتند. در روش غیرمستقیم نیز استان‌های قم، تهران و بوشهر در رتبه‌های برتر و چهارمحال و بختیاری، خراسان جنوبی و سیستان و بلوچستان در رتبه‌های پایین‌تر قرار گرفتند. نتایج حاکی از تمرکز تولید در مناطق خاصی از کشور و ضرورت توجه به سیاست‌های منطقه‌ای برای توسعه متوازن بود. این یافته‌ها می‌توانند راهنمای سیاست‌گذاران در تخصیص منابع و برنامه‌ریزی اقتصادی منطقه‌ای باشند. https://ijer.atu.ac.ir/article_20615_c54c66ec4b3b9e868020fbf8fa77d427.pdf