Global Marble Trade After China’s World Trade Organisation Membership: A Complex Network Approach

Öz

This study explores the evolution of the global marble trade network (GMTN) over the period 1995–2021, with a particular focus on structural changes linked to China’s accession to the World Trade Organisation (WTO) in 2001. By employing complex network analysis on a long-term temporal scale, the research documents the gradual transformation of the network and the increasing centrality of China within global marble trade flows. The results show that the post-2001 period is associated with a marked increase in trade integration, during which China moved from a relatively peripheral position towards a more central role in both raw and processed marble trade. Analysis of key network metrics—including density, centrality, and modularity—reveals notable shifts in network organisation following WTO accession, highlighting China’s growing structural embeddedness within global producer–consumer linkages. This research contributes to the literature by offering an empirical framework for understanding how significant institutional changes may be associated with the reorganisation of global natural resource trade networks.

Anahtar Kelimeler

• Marble
• Complex Network Analysis
• World Trade Organisation
• China
• International Trade

Kaynakça

1. Agarwal, J. & Wu, T. (2004). China’s entry to WTO: Global marketing issues, impact, and implications for China. International Marketing Review, 21(3), 279–300. https://doi.org/10.1108/02651330410539620 google scholar
2. Bishop, M. L. & Xiaotong, Z. (2020). Why is China a reluctant leader of the World Trade Organization? New Political Economy, 25(5), 755–772. https://doi.org/10.1080/13563467.2019.1584170 google scholar
3. 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), 1–12. https://doi.org/10.1088/1742-5468/2008/10/P10008 google scholar
4. Bulut, C., Aka, S. P. & Nazli, M. (2021). Strategic orientations toward technological innovativeness in the marble industry. SN Business & Economics, 1(10), 1–14. https://doi.org/10.1007/s43546-021-00127-9 google scholar
5. Cong, Y., Hou, Y., Jiang, J., Chen, S. & Cai, X. (2023). Features and evolution of global energy trade patterns from the perspective of complex networks. Energies, 16(15), 1–17. https://doi.org/10.3390/en16155677 google scholar
6. Cui, H. (2022). Analysis Model Design on the Influencing Factors and Countermeasures of China’s International Trade Facing the Belt and Road. Scientific Programming, 2022(1). https://doi.org/10.1155/2022/4927610 google scholar
7. Efe, T., & Sallan, S. (2017). Türkiye’de Doğal Taş Sanayinin Coğrafi ve Ekonomik Sürdürülebilirliği. Akademia Doğa ve İnsan Bilimleri Dergisi, 3(1), 173-181. google scholar
8. Farooq, A., Ashfaq, N., Majeed, S. & Ali, S. (2018). Prediction of top trade-leading countries through social network analysis using hybrid classification techniques. In 2018 IEEE 21st International Multi-Topic Conference (INMIC) (pp. 1–6). https://doi.org/10.1109/INMIC.2018.8595689 google scholar

9. Fitch. (2023, June 20). Megatrends to 2050: How global economic rankings will change [Web page]. Retrieved fromhttps://www.fitchsolutions.com/country-risk/megatrends-2050-how-global-economic-rankings-will-change-20-06-2023 google scholar
10. Fruchterman, T. M. J., & Reingold, E. M. (1991). Graph drawing by force-directed placement. Software: Practice and Experience, 21(11), 1129–1164. https://doi.org/10.1002/spe.4380211102 google scholar
11. Gan, J. (2004). Effects of China’s WTO accession on global forest product trade. Forest Policy & Economics, 6(6), 509–519. https://doi.org/10.1016/S1389-9341(02)00118-1 google scholar
12. Ghali, N., Panda, M., Hassanien, A. E., Abraham, A. & Snasel, V. (2012). Social networks analysis: Tools, measures and visualization. In A. Abraham (Ed.), Computational social networks: Mining and visualization (pp. 3–23). London: Springer-Verlag London. https://doi.org/10.1007/978-1-4471-4054-2_1 google scholar
13. Goldman Sachs. (2022, December 6). The Path to 2075 — Slower Global Growth, But Convergence Remains Intact [Web page]. Retrieved from https://www.goldmansachs.com/insights/goldman-sachs-research/the-path-to-2075-slower-global-growth-but-convergence-remains-intact google scholar
14. González, R.F. (2008). La Piedra Natural y el Patrimonio construido: Un mismo campo de investigación. Materiales De Construccion, 58, 7-10. google scholar
15. Hanieh, A. A., AbdElall, S. & Hasan, A. (2014). Sustainable development of the stone and marble sector in Palestine. Journal of Cleaner Production, 84, 581–588. https://doi.org/10.1016/j.jclepro.2013.10.045 google scholar
16. Hao, X., An, H., Sun, X. & Zhong, W. (2018). Import competition intensity in the international iron ore trade: A network perspective. Resources Policy, 57, 45–54. https://doi.org/10.1016/j.resourpol.2018.01.005 google scholar
17. Herman, P. R. (2022). Modeling complex network patterns in international trade. Review of World Economics, 158(1), 127–179. https://doi.org/10.1007/s10290-021-00429-y google scholar
18. Hossain, M. M. & Alam, S. (2017). A complex network approach toward modeling the Australian airport network. Journal of Air Transport Management, 60, 1–9. https://doi.org/10.1016/j.jairtraman.2016.12.008 google scholar
19. Kim, M. & Xin, D. (2021). Export spillover from foreign direct investment in China during pre-and post-WTO accession. Journal of Asian Economics, 75, 101337. https://doi.org/10.1016/j.asieco.2021.101337 google scholar
20. Li, Y. & Bai, Y. (2023). Research on the impact of global economic policy uncertainty on manufacturing: Evidence from China, the United States, and the European Union. Sustainability, 15(14). https://doi.org/10.3390/su151411217 google scholar
21. Liu, J., Xiong, Q., Shi, W. & Wang, K. (2016). Evaluating the importance of nodes in complex networks. Physica A: Statistical Mechanics and Its Applications, 452, 209–219. http://dx.doi.org/10.1016/j.physa.2016.02.049 google scholar
22. Liu, Q., Liu, Y. & Zhang, J. (2022). The tourism service trade network: Evidence from China and ASEAN countries. Sustainability, 14(16), 1–18. https://doi.org/10.3390/su14169950 google scholar
23. Lu, L. & Keller, A. (2022). Is it China’s Lehman Brothers moment? Unveiling the Evergrande debt crisis, financial risks and regulatory implications. Law and Financial Markets Review, 16(1–2), 133–144. https://doi.org/10.1080/17521440.2022.2150524 google scholar
24. Prasad, E. (2004, June 2). Growth and stability in China [Remarks at the plenary panel of the Harvard China Review Annual Conference]. Retrieved from https://www.imf.org google scholar
25. Sajedianfard, N., Hadian, E., Samadi, A. H., Dehghan Shabani, Z., Sarkar, S. & Robinson, P. A. (2021). Quantitative analysis of trade networks: Data and robustness. Applied Network Science, 6(1), 1–26. https://doi.org/10.1007/s41109-021-00386-3 google scholar
26. Soh, H., Lim, S., Zhang, T., Fu, X., Lee, G. K. K., Hung, T. G. G., … & Wong, L. (2010). Weighted complex network analysis of travel routes on the Singapore public transportation system. Physica A: Statistical Mechanics and Its Applications, 389(24), 5852–5863. https://doi.org/10.1016/j.physa.2010.08.015 google scholar
27. Soyyigit, S., Topuz, H., & Özekicioğlu, H. (2020). An Alternative View to the Global Coal Trade: Complex Network Approach. Studies in Business and Economics, 15(1). https://doi.org/10.2478/sbe-2020-0020 google scholar
28. StoneNews (2025, May 14). China Turns a Page in Marble Imports [Web page]. Retrieved from https://stonenews.eu/china-turns-a-page-in-marble-imports-new-q1-2025-report-by-stonenews-eu/ google scholar
29. Tang, M. K. & Wei, S. J. (2009). The value of making commitments externally: Evidence from WTO accessions. Journal of International Economics, 78(2), 216–229. https://doi.org/10.1016/j.jinteco.2009.01.008 google scholar
30. Thasni, M. A. & George, S. (2022). Structural analysis of air transport network using network indicators. IPRECON, 1–6. https://doi.org/10.1109/IPRECON55716.2022.10059483 google scholar
31. The World Bank. (n.d.). GDP growth (annual %) – China [Web page]. Retrieved August 5, 2024, from https://data.worldbank.org/indicator/NY.GDP.MKTP.KD.ZG?locations=CN google scholar
32. Trucmel, I. M., Vintila, A., Capbun, A. G. & Roman, M. D. (2022). An international trade disputes analysis using network theory. Proceedings of the International Conference on Business Excellence, 16(1), 639–649. https://doi.org/10.2478/picbe-2022-0061 google scholar
33. UN Comtrade. (n.d.). Trade Data [Web page]. Retrieved May 25, 2024, from https://comtradeplus.un.org/ google scholar
34. Wang, W., Li, Z. & Cheng, X. (2019). Evolution of the global coal trade network: A complex network analysis. Resources Policy, 62, 496–506. https://doi.org/10.1016/j.resourpol.2018.10.005 google scholar
35. Wang, Z. (2003). The impact of China’s WTO accession on patterns of world trade. Journal of Policy Modeling, 25(1), 1–41. https://doi.org/10.1016/S0161-8938(02)00196-5 google scholar
36. Williams, S., Xu, W., Tan, S. B., Foster, M. J. & Chen, C. (2019). Ghost cities of China: Identifying urban vacancy through social media data. Cities, 94, 275–285. https://doi.org/10.1016/j.cities.2019.05.006. google scholar
37. WTO. (n.d.). What we stand for [Web page]. Retrieved June 23, 2024, from https://www.wto.org/english/thewto_e/whatis_e/what_stand_for_e.html google scholar
38. Wu, X. (2011). No longer outside, not yet equal: Rethinking China’s membership in the World Trade Organization. Chinese Journal of International Law, 10(2), 227–270. https://doi.org/10.1093/chinesejil/jmq034 google scholar
39. Xu, H. & Cheng, L. (2016). The QAP weighted network analysis method and its application in international services trade. Physica A: Statistical Mechanics and Its Applications, 448, 91–101. https://doi.org/10.1016/j.physa.2015.12.094 google scholar
40. Yang, Y. & Yang, H. (2008). Complex network-based time series analysis. Physica A: Statistical Mechanics and Its Applications, 387(5–6), 1381–1386. https://doi.org/10.1016/j.physa.2007.10.055 google scholar
41. Zhong, W., An, H., Fang, W., Gao, X., & Dong, D. (2016). Features and evolution of international fossil fuel trade network based on value of emergy. Applied Energy, 165, 868-877. https://doi.org/10.1016/j.apenergy.2015.12.083 google scholar
42. Zhu, M., Zhou, X., Zhang, H., Wang, L. & Sun, H. (2023). International trade evolution and competition prediction of boron ore: Based on complex network and link prediction. Resources Policy, 82, 1–14. https://doi.org/10.1016/j.resourpol.2023.103542 google scholar
43. Zhu, X. (2012). Understanding China’s growth: Past, present, and future. Journal of Economic Perspectives, 26(4), 103–124. https://doi.org/10.1257/jep.26.4.103 google scholar