Economic Strategy

Economic Strategy

The Role of Resource Dependence and Complex Network Theory in the Formation of International Trade Blocs(oil countries of the Persian Gulf)

Document Type : Original Article

Author
mostafa heidari haratemeh
Associate Professor, Department of Economics and Management, Naragh Branch, Islamic Azad University, Naragh, Iran
10.22034/es.2024.405116.1687
Abstract
According to the resource dependence theory, if a country is dependent on certain resources, then it will be influenced by other related countries in that trade sector.  On the other hand, in commercial interactions, with the increase in the number of countries and relations between them, the formation and management of commercial blocs becomes a complex issue.  In this regard, the formation of trade communities/blocs can be a strategy to reduce restrictions and increase trade interactions and its security through close communication between countries. Therefore, the research question implies the role of the theory of resource dependence and complex network in the formation of commercial blocs. The purpose of the present study was to investigate the role of resource dependence theory and complex network theory in the formation of international trade blocs in line with the integration of the global economy. The data of the research variables were extracted from the oil countries of the Persian Gulf and active in international trade and based on the availability of the data of the United Nations database (COMTRADE) in a period of 2006-2021, due to the large amount of data, 20 countries were used as samples were chosen to account for the maximum volume of this international trade. Negative binomial regression was used to analyze the data and estimate the model. The results showed:  When a country cooperates with a large number of trading partners or has a dominant position in the international trade network, it is more likely that other countries will form identical blocs with that country. Also, if a country with a central network position needs to obtain important resources from other countries in trade blocs, then the desire of this country to participate in larger trade blocs with other countries will be much higher. In fact, network location can strengthen the effect of resource dependence in the formation of trade blocs.
Keywords
Complex Network Theory
International Trade
Resource Dependence Theory
Trade Community

Subjects

Agranoff, R. & Clift, S. (2013). Burt, R.S. (1992). Structural holes: the social structure of competition. Ca mbridge, MA, Harvard.
An, H.; Gao, X.; Fang, W.; Ding, Y. & Zhong, W. (2014a). Research on patterns in the fl uctuation of the comovement between crude oil futures and spot prices: a complex network approach. Appl. Energy (136), 1067-1075.
Barber, M.J. (2007). Modularity and community detection in bipartite networks. Phys. Rev. E Stat. Nonlinear Soft Matter Phys, (76(, 066102.
Brada, J.C. & Méndez, J.A. (1985). Economic integration among developed, developing and centrally planned economies: a comparative analysis. Rev. Econ. Stat, (67), 549-556.
Brandes, U. (2001). A faster algorithm for betweenness centrality. J. Math. Sociol, (25), 163-177.
Burt, R.S. (2010). Structural Holes: The Social Structure of Competition. Harvard University Press.
Chai, R.; Chen, M.; Chen, Q. & Gao, Y. (2017). An optimal joint user association and power allocation algorithm for secrecy information transmission in heterogeneous networks. Wirel. Commun. Mob. Comput. 2017, 13.
Chang, T.Y.; Hsu, T.C. & Hong, Y.W.P. (2010). Exploiting data-dependent transmission control and MAC timing information for distributed detection in sensor networks. IEEE Trans. Signal Process, (58), 1369-1382.
Dong, D.; An, H. & Huang, S. (2017). The transfer of embodied carbon in copper international trade: an industry chain perspective. Resour. Policy (52), 173-180.
Fan, Y.; Ren, S.; Cai, H. & Cui, X. (2014). The state's role and position in international trade: a complex network perspective ☆. Econ. Model, (39), 71-81.
Freeman, L.C. (1977). A set of measures of centrality based on betweenness. Sociometry, (40), 35-41.
Gao, X.; An, H.; Fang, W.; Li, H. & Sun, X. (2014). The transmission of fluctuant patterns of the forex burden based on international crude oil prices. Energy, (73), 380-386.
Gao, X.; Fang, W.; An, F. & Wang, Y. (2017). Detecting method for crude oil price fluctuation mechanism under different periodic time series. Appl. Energy, (192), 201-212.
Garlaschelli, D.; Matteo, T.D.; Aste, T.; Caldarelli, G. & Loffredo, M.I. (2007). Interplay between topology and dynamics in the World Trade Web. Eur. Phys. J. B (57),159-164.
Guan, Q.; An, H.; Gao, X.; Huang, S. & Li, H. (2016). Estimating potential trade links in the international crude oil trade: a link prediction approach. Energy, (102), 406-415.
Hasson, J.A. & Tinbergen, J. (1962). Shaping the world economy: suggestions for an international economic policy. Economica, (31).
Hillman, A.J.; Withers, M.C. & Collins, B.J. (2009). Resource dependence theory: a review. J. Manag, (35), 1404-1427.
Hinkelman, E.G. & Shippey, K.C. (2002). Dictionary of International Trade: Handbook of the Global Trade Community Includes 19 Key Appendices.
Huang, S.; An, H.; Viglia, S.; Buonocore, E.; Fang, W. & Ulgiati, S. (2017). Revisiting ChinaAfrica trade from an environmental perspective. J. Clean. Prod. (167), 553-570.
Ji, Q.; Zhang, H.Y. & Fan, Y. (2014). Identification of global oil trade patterns: an empirical research based on complex network theory. Energy Convers. Manag, (85), 856-865.
Kuznets, S. (2002). Economic growth and income inequality. Am. Econ. Rev. (55), 1-28.
Leicht, E.A. & Newman, M.E.J. (2008). Community structure in directed networks. Phys. Rev. Lett. (100), 118703.
Linnemann, H. (1966). An Econometric Study of International Trade Flows. North-Holland Pub. Co.
Milo, R.; Shenorr, S.; Itzkovitz, S.; Kashtan, N.; Chklovskii, D. & Alon, U. (2002). Network motifs: simple building blocks of complex networks. Science 298.
Newman, M.E.J. (2004). Fast algorithm for detecting community structure in networks. Phys. Rev. E 69, 066133.
Ozmel, U.; Reuer, J.J. & Gulati, R. (2013). Signals across multiple networks:: how venture capital and alliance networks affect interorganizational collaboration. Acad. Manag. J. (56), 852-866.
Pfeffer, J. & Salancik, G.R. (2003). The External Control of Organizations: A Resource Dependence Perspective. 23. Social Science Electronic Publishing, 123-133.
Qin, Z.; Zhang, J. & Wang, J. (2008). Enhanced reliable transmission control protocol for spatial information networks. J. Commun. (82), 130-143.
Rubinov, M. & Sporns, O. (2010). Complex network measures of brain connectivity: uses and interpretations. Neuroimage, (52), 1059-1069.
Sabidussi, G. (1966). The centrality index of a graph. Psychometrika, (31), 581-603.
Schwarz, A.J.; Gozzi, A. & Bifone, A. (2008). Community structure and modularity in networks of correlated brain activity. Magn. Reson. Imaging 26, 914.
Shipilov, A.V. (2009). Firm scope experience, historic multimarket contact with partners, centrality, and the relationship between structural holes and performance. Organ. Sci. (20), 85-106.
Smith, S.M. & Dorward, P.T. (2014). Nationalised large-scale mining, trade unions and community representation: perspectives from Northern Madagascar. Resour. Policy, (40), 31-41.
Sonora, R.J. (2008). On the impacts of economic freedom on International trade flows: asymmetries and Freedom components. General. Inf. Tehseen, S., Sajilan, S., 2016. Network competence based on resource-based view and resource dependence theory. Int. J. Trade Glob. Mark. (9), 60-82.
Trojan, C. (1986). [Milk policy and the role of the Community in the international trade]. German: Molkerei Zeitung.
Tzekina, I.; Danthi, K. & Rockmore, D.N. (2008). Evolution of community structure in the world trade web. Eur. Phys. J. B (63), 541-545.
Vickmajors, T.J.; Priscu, J.C. & Amaralzettler, L.A. (2014). Modular community structure suggests metabolic plasticity during the transition to polar night in ice-covered Antarctic lakes. ISME J. 8, 778.
Westphal, J.D.; Boivie, S. & Chng, D.H.M. (2006). The strategic impetus for social network ties: reconstituting broken CEO friendship ties. Strateg. Manag. J. (27), 425-445.
Xia, J.; Wang, Y.; Lin, Y.; Yang, H. & Li, S. (2016). Alliance formation in the midst of market and network: insights from resource dependence and network perspectives. J. Manag.
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.
Zhong, W.; An, H.; Gao, X. & Sun, X. (2014). The evolution of communities in the international oil trade network. Phys. A Stat. Mech. Appl. (413), 42-52.
Zhong, W.; An, H.; Shen, L.; Dai, T.; Fang, W.; Gao, X. & Dong, D. (2017). Global pattern of the international fossil fuel trade: the evolution of communities. Energy, (123), 260.

  • Receive Date 02 July 2023
  • Revise Date 06 November 2023
  • Accept Date 26 November 2023