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تحلیل الگوی شبکه تجارت جهانی نفت: رویکرد شبکه پیچیده | ||
| مدلسازی اقتصادسنجی | ||
| مقاله 5، دوره 8، شماره 2 - شماره پیاپی 30، شهریور 1402، صفحه 121-162 اصل مقاله (8.88 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22075/jem.2023.29961.1813 | ||
| نویسندگان | ||
| روح اله شهنازی* 1؛ نجمه ساجدیان فرد2 | ||
| 1دانشیار اقتصاد، بخش اقتصاد، دانشگاه شیراز | ||
| 2پژوهشگر پسادکتری، بخش اقتصاد، دانشگاه شیراز | ||
| تاریخ دریافت: 17 اسفند 1401، تاریخ بازنگری: 12 تیر 1402، تاریخ پذیرش: 21 تیر 1402 | ||
| چکیده | ||
| پبچیدگی فزاینده الگوی تجارت جهانی نفت یکی از مهمترین عوامل تأثیرگذار بر راهبرد انرژی و توسعه اقتصادی هر کشور، به خصوص کشورهای صادرکننده نفت مانند ایران، است. در این مقاله، ویژگی‌های کلی، ویژگی‌های منطقه‌ای و استحکام تجارت نفت با استفاده از نظریه شبکه برای 178 کشور در سال 2018 تجزیه و تحلیل شده است. نتایج حاکی از آن است که شبکه صادرات نفت توزیع مقیاس آزاد دارد بدین معنا که موقعیت تجاری کشورها ناهمگونی آشکاری را نشان می‌دهد. به علاوه، شبکه تجارت جهانی نفت ویژگی «مستحکم اما در عین حال شکننده» دارد. همچنین شبکه تجارت جهانی نفت به سه بلوک تجاری شامل بلوک مرکزی و شرقی تجاری، بلوک میانی تجاری و بلوک غربی تجاری قابل تقسیم است. در بین این سه بلوک تجاری، بلوک مرکزی و شرقی توانسته است بیشترین میزان تأمین تقاضای کشورهای حاضر در این بلوک را تأمین کند و بنابراین این کشورها از کمترین تکانههای عرضه نفت برخوردار میشوند. | ||
| کلیدواژه‌ها | ||
| تجارت جهانی نفت؛ نظریه شبکه؛ پایداری؛ استحکام | ||
| عنوان مقاله [English] | ||
| Pattern of Global Oil Trade Network: A Network Theory Approach | ||
| نویسندگان [English] | ||
| Rouhollah Shahnazi1؛ Najmeh Sajedianfard2 | ||
| 1Associate professor in Economics, Department of Economics, Shiraz University | ||
| 2Postdoctoral researcher in Economics, Department of Economics, Shiraz University | ||
| چکیده [English] | ||
| The increasing complexity of the global oil trade significantly affects the energy strategy and economic development of countries, particularly those that export oil, such as Iran. This paper analyzes the general characteristics, regional features, and strength of the oil trade using network theory for 178 countries in 2018. The results show that the oil export network has a free-scale distribution, which means that the commercial position of countries displays significant heterogeneity. Additionally, the global oil trade network has a "robust yet fragile" characteristic. The global oil trade network can be divided into three commercial blocks, including the central and eastern commercial block, the middle commercial block, and the western commercial block. Among these three commercial blocs, the central and eastern bloc can supply the highest amount of demand from the countries present in this bloc. Consequently, these countries receive the lowest oil supply impulses. | ||
| کلیدواژه‌ها [English] | ||
| Oil trade, network theory, sustainability | ||
| مراجع | ||
|
An, H., Zhong, W., Chen, Y., Li, H. & Gao, X. (2014), Features and evolution of international crude oil trade relationships: A trading-based network analysis. Energy, 74, 254-259.
Ashfaq, S., Tang, Y. & Maqbool, R. (2020), Dynamics of spillover network among oil and leading Asian oil trading countries’ stock markets, Energy, 207: 118077.
Asia Pacific Energy Research Centre. A quest for energy security in the 21st century. Tokyo: Institute of Energy Economics, Asia Pacific Energy Research Centre; 2007
Barabási, A. L. (2016), Network science. Cambridge, United Kingdom: Cambridge university press.
Blondel, V. D., Guillaume, J. L., Lambiotte, R. & Lefebvre, E. (2008), Fast unfolding of communities in large networks, Journal of statistical mechanics: theory and experiment, 2008(10): P10008.
British Petroleum (2017), BP statistical review of world energy. In Tech rep British Petroleum, London, UK.
British Petroleum, BP Statistical review of the world energy 2020. London: BP; 2020.
Dong, G., Qing, T., Du, R., Wang, C., Li, R., Wang, M., Tian, L., Chen, L., Vilela, A. L. M. & Stanley, H. E. (2020), Complex network approach for the structural optimization of global crude oil trade system, Journal of Cleaner Production, 251: 119366.
Du, R., Dong, G., Tian, L., Wang, Y., Liu, Y., Wang, M. & Fang, G. (2016), A complex network perspective on features and evolution of world crude oil trade, Energy Procedia, 104: 221-226.
Du, R., Wang, Y., Dong, G., Tian, L., Liu, Y., Wang, M. & Fang, G. (2017), A complex network perspective on interrelations and evolution features of international oil trade, 2002–2013, Applied Energy, 196: 142-151.
Fath, B. D., Dean, C. A. & Katzmair, H. (2015), Navigating the adaptive cycle: an approach to managing the resilience of social systems, Ecology and Society, 20(2).
Folke, C., Carpenter, S. R., Walker, B., Scheffer, M., Chapin, T. & Rockström, J. (2010), Resilience thinking: integrating resilience, adaptability and transformability, Ecology and society, 15(4).
Folke, C., Carpenter, S., Walker, B., Scheffer, M., Elmqvist, T., Gunderson, L. & Holling, C. S. (2004), Regime shifts, resilience, and biodiversity in ecosystem management, Annu. Rev. Ecol. Evol. Syst., 35: 557-581.
Holling, C. S. & Gunderson, L. H. (2002), Resilience and adaptive cycles, In: Panarchy: Understanding Transformations in Human and Natural Systems, 25-62.
Hughes, L. (2012), A generic framework for the description and analysis of energy security in an energy system, Energy Policy, 42: 221-231.
International Energy Agency. Toward a sustainable energy future. Paris: International Energy Agency; 2001.
Jackson, M. O. (2010), Social and economic networks, Princeton and Oxford, United States of America and United Kingdom: Princeton university press.
Ji, Q., Zhang, H. Y. & Fan, Y. (2014), Identification of global oil trade patterns: An empirical research based on complex network theory, Energy Conversion and Management, 85: 856-865.
Kharrazi, A., Sato, M., Yarime, M., Nakayama, H., Yu, Y. & Kraines, S. (2015), Examining the resilience of national energy systems: Measurements of diversity in production-based and consumption-based electricity in the globalization of trade networks, Energy Policy, 87: 455-464.
Kitamura, T. & Managi, S. (2017), Driving force and resistance: Network feature in oil trade, Applied Energy, 208: 361-375.
Klimek, P., Varga, J., Jovanovic, A. S. & Székely, Z. (2019), Quantitative resilience assessment in emergency response reveals how organizations trade efficiency for redundancy, Safety science, 113: 404-414.
LaCasse, C. & Plourde, A. (1995), On the renewal of concern for the security of oil supply, The Energy Journal, 16(2).
Liu, L., Cao, Z., Liu, X., Shi, L., Cheng, S. & Liu, G. (2020), Oil security revisited: An assessment based on complex network analysis, Energy, 194: 116793.
Newman, M. E. (2003), The structure and function of complex networks, SIAM review, 45(2): 167-256.
Newman, M. E. (2010), Networks: An introduction, Oxford, United Kingdom: Oxford university press.
Önder, A. S. & Yilmazkuday, H. (2016), Trade partner diversification and growth: How trade links matter, Journal of Macroeconomics, 50: 241-258.
Reichardt, J. & Bornholdt, S. (2006), Statistical mechanics of community detection, Physical review E, 74(1): 016110.
Ronhovde, P. & Nussinov, Z. (2009), Multiresolution community detection for megascale networks by information-based replica correlations, Physical Review E, 80(1): 016109.
Shirazi, M., Ghasemi, A., Mohammadi, T., Šimurina, J., Faridzad, A. & Taklif, A. (2020), A Dynamic Network Comparison Analysis of Crude Oil Trade: Evidence from Eastern Europe and Eurasia, Zagreb International Review of Economics & Business, 23(1): 95-119.
Song, Z., Zhu, Q. & Han, M. (2021), Tele-connection of global crude oil network: Comparisons between direct trade and embodied flows, Energy, 217: 119359.
Thoma, K. (2014), Resilience-by-Designˮ: Strategie für die technologischen Zukunftsthemen, Acadech Studie, München.
Von Hippel, D., Suzuki, T., Williams, J. H., Savage, T. & Hayes, P. (2011), Energy security and sustainability in Northeast Asia, Energy policy, 39(11): 6719-6730.
Wang, M., Tian, L. & Du, R. (2016), Research on the interaction patterns among the global crude oil import dependency countries: A complex network approach, Applied Energy, 180: 779-791.
Watts, D. J. & Strogatz, S. H. (1998), Collective dynamics of ‘small-world’ networks, Nature, 393(6684): 440.
Xi, X., Zhou, J., Gao, X., Liu, D., Zheng, H. & Sun, Q. (2019), Impact of changes in crude oil trade network patterns on national economy, Energy Economics, 84: 104490.
Yang, Y., Poon, J. P., Liu, Y. & Bagchi-Sen, S. (2015), Small and flat worlds: A complex network analysis of international trade in crude oil, Energy, 93: 534-543.
Zekri, H., Mokhtari, A. R. & Cohen, D. R. (2016), Application of singular value decomposition (SVD) and semi-discrete decomposition (SDD) techniques in clustering of geochemical data: an environmental study in central Iran, Stochastic environmental research and risk assessment, 30: 1947-1960.
Zhang, C., Fu, J. & Pu, Z. (2019), A study of the petroleum trade network of countries along “The Belt and Road Initiative”, Journal of Cleaner Production, 222: 593-605.
Zhang, H. Y., Ji, Q. & Fan, Y. (2014), Competition, transmission and pattern evolution: A network analysis of global oil trade, Energy Policy, 73: 312-322. | ||
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