Prioritizing China’s public policy options in developing logistics infrastructure under the Belt and Road Initiative


One of the aims of the Belt and Road Initiative (BRI), proposed by China in 2013, is to promote the development of logistics along corridor countries by eliminating trade barriers between countries along the corridor and by advancing the construction of port infrastructure and related facilities to improve maritime logistics. Financial integration, people-to-people bonds, policy coordination, facilities connectivity, and unimpeded trade are five major enabling factors of the BRI for enhancing logistics cooperation and service level among corridor countries. This paper aims to evaluate the importance of these factors, which allegedly influence logistics infrastructure development, from the perspective of public policy. The consistent fuzzy preference relations (CFPR) method is employed to determine the prioritization of the five logistics-enabling factors. Our results show that the factor unimpeded trade is ranked first, while the factor people-to-people bonds is ranked last. To further analyze the results, cross-sectional analysis between government officers and academics is conducted to clearly identify their preferences as well as differences of opinion. As expected, government officers prefer more of the factor policy coordination, while academics ascribe more importance to the factor unimpeded trade. Our findings can advise the Chinese government, the Asian Infrastructure Investment Bank (AIIB), and other corridor countries on how to prioritize their investments in order to develop logistics infrastructure and ensure the successful implementation of the BRI.

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  1. Chang, T.H., S.C. Hsu, and T.C. Wang. 2013. A proposed model for measuring the aggregative risk degree of implementing an RFID digital campus system with the consistent fuzzy preference relations. Applied Mathematical Modelling 37 (5): 2605–2622.

    Article  Google Scholar 

  2. Chang, T.H., and T.C. Wang. 2009. Measuring the success possibility of implementing advanced manufacturing technology by utilizing the consistent fuzzy preference relations. Expert Systems with Applications 36 (3): 4313–4320.

    Article  Google Scholar 

  3. Chen, S.M., T.E. Lin, and L.W. Lee. 2014. Group decision making using incomplete fuzzy preference relations based on the additive consistency and the order consistency. Information Sciences 259: 1–15.

    Article  Google Scholar 

  4. Dang, V.L., and G.T. Yeo. 2018. Weighing the key factors to improve Vietnam’s logistics system. The Asian Journal of Shipping and Logistics 34 (4): 308–316.

    Article  Google Scholar 

  5. Dumitrescu, G.C. 2015. Central and Eastern European countries focus on the Silk Road economic belt. Global Economic Observer 3 (1): 144–153.

    Google Scholar 

  6. Fallon, T. 2015. The new Silk Road: Xi Jinping’s grand strategy for Eurasia. American Foreign Policy Interests 37 (3): 140–147.

    Article  Google Scholar 

  7. Herrera-Viedma, E., F. Herrera, F. Chiclana, and M. Luque. 2004. Some issues on consistency of fuzzy preference relations. European Journal of Operational Research 154 (1): 98–109.

    Article  Google Scholar 

  8. Hong Kong Trade Development Council (HKTDC). 2016. Accessed 29 Nov 2016.

  9. Huang, Y. 2016. Understanding China’s Belt & Road initiative: motivation, framework and assessment. China Economic Review 40: 314–321.

    Article  Google Scholar 

  10. Karim, M.A. 2015. China’s proposed maritime Silk Road: challenges and opportunities with special reference to the Bay of Bengal region. Pacific Focus: Inha Journal of International Studies 30 (3): 297–319.

    Article  Google Scholar 

  11. Lee, P.T.W., C.W. Lin, and Y.S. Chung. 2014. Comparison analysis for subjective and objective weights of financial positions of container shipping companies. Maritime Policy & Management 41 (3): 241–250.

    Article  Google Scholar 

  12. Li, P., H. Qian, K.W.F. Howard, and J. Wu. 2015. Building a new and sustainable Silk Road economic belt. Environmental Earth Sciences 74 (10): 7267–7270.

    Article  Google Scholar 

  13. Li, Y.Q. and X.Q. Wang. 2016. Annual Report on Development of “the belt and road” construction. Accessed 29 Nov 2016.

  14. Lim, A.C.H. 2015. Africa and China’s 21st century maritime Silk Road. The Asia-Pacific Journal: Japan Focus 13: 1–19.

    Google Scholar 

  15. Mao, J.H. 2015. Advantage analysis of industrial space of the Silk Road economic belt. Global Journal of Management and Business Research 15 (1): 1–4.

    Google Scholar 

  16. Peyrousea, S., and G. Raballand. 2015. Central Asia: The new Silk Road initiative’s questionable economic rationality. Eurasian Geography and Economics 56 (4): 405–420.

    Article  Google Scholar 

  17. Rolland, N. 2015. China’s New Silk Road. The National Bureau of Asian Research, Seattle, US, 1–3. Accessed 5 Oct 2016.

  18. Swaine, M.D. 2015. Chinese views and commentary on the “One Belt, One Road” initiative. China Leadership Monitor 47 (2): 1–24.

    Google Scholar 

  19. Switalski, Z. 2001. Transitivity of fuzzy preference relations—An empirical study. Fuzzy Sets and Systems 118 (3): 503–508.

    Article  Google Scholar 

  20. Switalski, Z. 2003. General transitivity conditions for fuzzy reciprocal preference matrices. Fuzzy Sets and Systems 137 (1): 85–100.

    Article  Google Scholar 

  21. Tanino, T. 1984. Fuzzy preference orderings in group decision making. Fuzzy Sets and Systems 12 (2): 117–131.

    Article  Google Scholar 

  22. Thakur, R. 2015. One belt, one road: China’s new strategic and trade policy. Delhi Policy Group. Accessed 30 Mar 2016.

  23. Tsai, J.Y., J.F. Ding, and K.D. Ye. 2018. Use of a hybrid MCDM method to evaluate key solutions influencing service quality at a port logistics center in Taiwan. Brodogradnja 69 (1): 89–105.

    Article  Google Scholar 

  24. Wang, T.C., and Y.L. Lin. 2009. Applying the consistent fuzzy preference relations to select merger strategy for commercial banks in new financial environments. Expert Systems with Applications 36 (3): 7019–7026.

    Article  Google Scholar 

  25. Xu, Z. 2006. Incomplete linguistic preference relations and their fusion. Information Fusion 7 (3): 331–337.

    Article  Google Scholar 

  26. Zhang, H.Z. and A. Guschin. 2015. China’s Silk Road Economic Belt: Geopolitical Challenges in Central Asia, S. Rajaratnam School of International Studies Commentary 099 (RSIS Commentaries, No. 099). Singapore: Nanyang Technological University.

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The authors are grateful to the editor and referees for their careful reading and many useful comments.

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Correspondence to Chien-Chang Chou.

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Wang, Y., Chou, C. Prioritizing China’s public policy options in developing logistics infrastructure under the Belt and Road Initiative. Marit Econ Logist 22, 293–307 (2020).

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  • Maritime logistics
  • Belt and road
  • Unimpeded trade
  • Facilities connectivity
  • Fuzzy theory
  • Consistent fuzzy preference relation