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Evaluation of the business environment of participating countries of the Belt and Road Initiative

    Zheng-Xin Wang Affiliation
    ; Wen-Qian Lou Affiliation
    ; Ling-Ling Pei Affiliation

Abstract

As an important indicator for measuring the quality of business environment of different countries, ease of doing business (EDB) issued by the World Bank (WB) provides an important reference for investors in making decisions on transnational investment. The calculation method for EDB issued by the WB is improved using a technique for order preference by similarity to an ideal solution (TOPSIS) method based on Mahalanobis distance. Based on various indicator data in 2019, business environments in 121 countries participating in “the Belt and Road Initiative (BRI)” were empirically analysed and compared through such models. The result showed that TOPSIS method based on Mahalanobis distance can more fully utilise information and take the effect of negative ideal points into account. Therefore, compared with ranking method by the WB, TOPSIS method based on Mahalanobis distance is more applicable for ranking BRI countries. The ranking results indicated significant geographical characteristics. The EDB rankings obtained through the WB overestimate the business environments of countries in Central and Eastern Europe while underestimate those in Southeast Asia, Africa, etc.


First published online 22 September 2020

Keyword : the Belt and Road initiative, TOPSIS, Mahalanobis distance, business environment

How to Cite
Wang, Z.-X., Lou, W.-Q., & Pei, L.-L. (2020). Evaluation of the business environment of participating countries of the Belt and Road Initiative. Technological and Economic Development of Economy, 26(6), 1339-1365. https://doi.org/10.3846/tede.2020.13454
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Nov 17, 2020
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References

Antuchevičienė, J., Zavadskas, E. K., & Zakarevičius, A. (2010). Multiple criteria construction management decisions considering relations between criteria. Technological and Economic Development of Economy, 16(1), 109–125. https://doi.org/10.3846/tede.2010.07

Bai, C., & Sarkis, J. (2018). Integrating sustainability into supplier selection: a grey-based TOPSIS analysis. Technological and Economic Development of Economy, 24(6), 2202–2224. https://doi.org/10.3846/tede.2018.5582

Belt and Road Portal. (n.d.). https://www.yidaiyilu.gov.cn/index.htm

Chang, C. H., Lin, J. J., Lin, J. H., & Chiang, M. C. (2010). Domestic open-end equity mutual fund performance evaluation using extended TOPSIS method with different distance approaches. Expert Systems with Applications, 37(6), 4642–4649. https://doi.org/10.1016/j.eswa.2009.12.044

Corcoran, A., & Gillanders, R. (2015). Foreign direct investment and the ease of doing business. Review of World Economics, 151, 103–126. https://doi.org/10.1007/s10290-014-0194-5

Cui, H. Y. (2016). Study on the trade & investment facilitation evaluation index system of countries of “one belt and one road”. Journal of International Trade, 9, 153–164.

Cullinane, K., Lee, P., Yang, Z., & Hu, Z. (2018). Editorial: China’s Belt and Road initiative. Journal of Asian Economics, 117, 1–4.

dos Santos, B., Godoy, L., & Campos, L. (2019). Performance evaluation of green suppliers using entropy-TOPSIS-F. Journal of Cleaner Production, 207, 498–509. https://doi.org/10.1016/j.jclepro.2018.09.235

Du, J., & Zhang, Y. (2018). Does One Belt One Road initiative promote Chinese overseas direct investment? China Economic Review, 47, 189–205. https://doi.org/10.1016/j.chieco.2017.05.010

Dwivedi, G., Srivastava, R., & Srivastava, S. (2018). A generalised fuzzy TOPSIS with improved closeness coefficient. Expert Systems with Applications, 96, 185–195. https://doi.org/10.1016/j.eswa.2017.11.051

Escaleras, M., & Chiang, E. (2017). Fiscal decentralization and institutional quality on the business environment. Economics Letters, 159, 161–163. https://doi.org/10.1016/j.econlet.2017.07.019

González-Arteaga, T., Alcantud, C., & Calle, R. (2016). A cardinal dissensus measure based on the Mahalanobis distance. European Journal of Operational Research, 251, 575–585. https://doi.org/10.1016/j.ejor.2015.11.019

Gupta, H. (2018). Assessing organizations performance on the basis of GHRM practices using BWM and Fuzzy TOPSIS. Journal of Environmental Management, 226, 201–216. https://doi.org/10.1016/j.jenvman.2018.08.005

Hamill, P., Giordano, M., Ward, C., Gile,s D., & Holben, B. (2016). An AERONET-based aerosol classification using the Mahalanobis distance. Atmospheric Environment, 140, 213–233. https://doi.org/10.1016/j.atmosenv.2016.06.002

Huang, Y. (2019). Environmental risks and opportunities for countries along the Belt and Road: Location choice of China’s investment. Journal of Cleaner Production, 211, 14–26. https://doi.org/10.1016/j.jclepro.2018.11.093

Hwang, C. L.; Lai, Y. J., & Liu, T. Y. (1993). A new approach for multiple objective decision making. Computers and Operational Research, 20(8): 889–899. https://doi.org/10.1016/0305-0548(93)90109-V

Hwang, C. L., & Yoon, K. (1981). Multiple attribute decision making: Methods and applications. Springer. https://doi.org/10.1007/978-3-642-48318-9

Jiang, Y., Zhang, J., Asante, D., & Yang, Y. (2019). Dynamic evaluation of low-carbon competitiveness (LCC) based on improved Technique for Order Preference by similarity to an Ideal Solution (TOPSIS) method: A case study of Chinese steelworks. Journal of Cleaner Production, 217, 484–492. https://doi.org/10.1016/j.jclepro.2019.01.054

Ke, T., Lv, H., Sun, M., & Zhang, L. (2018). A biased least squares support vector machine based on Mahalanobis distance for PU learning. Physica A: Statistical Mechanics and its Applications, 509, 422–438. https://doi.org/10.1016/j.physa.2018.05.128

Khan, B., Bilal, R., & Young, R. (2018). Fuzzy-TOPSIS based Cluster Head selection in mobile wireless sensor networks. Journal of Electrical Systems and Information Technology, 5, 928–943. https://doi.org/10.1016/j.jesit.2016.12.004

Kong, Q., & Dong, H. (2015). Trade facilitation and trade potential of countries along “One Belt One Road” route. Journal of International Trade, 12, 158–168.

Li, J., Liu, B., & Qian, G. (2019). The belt and road initiative, cultural friction and ethnicity: Their effects on the export performance of SMEs in China. Journal of World Business, 54, 350–359. https://doi.org/10.1016/j.jwb.2019.04.004

Lu, W., & Chen, W. (2018). Business environment, technological innovation and dynamic change of comparative advantage. International Economics and Trade Research, 11, 61–77.

Ouenniche, J., Pérez-Gladish, B., & Bouslah, K. (2018). An out-of-sample framework for TOPSIS-based classifiers with application in bankruptcy prediction. Technological Forecasting and Social Change, 131, 111–116. https://doi.org/10.1016/j.techfore.2017.05.034

Pelegrina, G., Duarte, L., & Romano, J. (2019). Application of independent component analysis and TOPSIS to deal with dependent criteria in multicriteria decision problems. Expert Systems with Applications, 122, 262. https://doi.org/10.1016/j.eswa.2019.01.008

Piwowarski, M., Miłaszewicz, D., Łatuszyńska, M., Borawski, M., & Nermend, K. (2018). TOPSIS and VIKOR methods in study of sustainable development in the EU countries. Procedia Computer Science, 126, 1683–1692. https://doi.org/10.1016/j.procs.2018.08.109

Qu, Z., & Yang, B. (2017). The influence of system quality of the countries along the “Belt and Road” on China’s foreign direct investment. Research on Economics and Management, 11, 15–21.

Shrestha, M. (2017). Cooperation on finance between China and Nepal: Belt and Road initiatives and investment opportunities in Nepal. The Journal of Finance and Data Science, 3, 31–37. https://doi.org/10.1016/j.jfds.2017.09.004

Sirisawat, P., & Kiatcharoenpol, T. (2018). Fuzzy AHP-TOPSIS approaches to prioritizing solutions for reverse logistics barriers. Computers & Industrial Engineering, 117, 303–318. https://doi.org/10.1016/j.cie.2018.01.015

Sun, L., Miao, C., & Yang, L. (2017). Ecological-economic efficiency evaluation of green technology innovation in strategic emerging industries based on entropy weighted TOPSIS method. Ecological Indicators, 73, 554–558. https://doi.org/10.1016/j.ecolind.2016.10.018

Tang, H., Shi, Y., & Dong, P. (2018). Public blockchain evaluation using entropy and TOPSIS. Expert Systems with Applications, 117, 204–210. https://doi.org/10.1016/j.eswa.2018.09.048

The World Bank. (2018). Doing Business 2019: Training for Reform. The World Bank Group, Washington DC. https://www.doingbusiness.org/content/dam/doingBusiness/media/Annual-Reports/English/DB2019-report_web-version.pdf

Vidal, R., & Sánchez-Pantoja, N. (2019). Method based on life cycle assessment and TOPSIS to integrate environmental award criteria into green public procurement. Sustainable Cities and Society, 44, 465–474. https://doi.org/10.1016/j.scs.2018.10.011

Walczak, D., & Rutkowska, A. (2017). Project rankings for participatory budget based on the fuzzy TOPSIS method. European Journal of Operational Research, 260, 706–714. https://doi.org/10.1016/j.ejor.2016.12.044

Wang, Z., Hao, H., Gao, F., Zhang, Q., Zhang, J., & Zhou, Y. (2019). Multi-attribute decision making on reverse logistics based on DEA-TOPSIS: A study of the Shanghai end-of-life vehicles industry. Journal of Cleaner Production, 214, 730–737. https://doi.org/10.1016/j.jclepro.2018.12.329

Wang, Z., Li, D., & Zheng, H. (2018). The external performance appraisal of China energy regulation: An empirical study using a TOPSIS method based on entropy weight and Mahalanobis distance. International Journal of Environmental Research and Public Health, 15, 235–251. https://doi.org/10.3390/ijerph15020236

Wang, Z., & Wang, Y. (2014). Evaluation of the provincial competitiveness of the Chinese high-tech industry using an improved TOPSIS method. Expert Systems with Applications, 41, 2824–2831. https://doi.org/10.1016/j.eswa.2013.10.015

Xu, Y., Cui, R., & Bao, Y. (2015). Influence factors of Russian regional investment environment that improve level of FDI inflow: Based on dynamic panel analysis estimated by system GMM method. International Business, 06, 57–113.

Yan, Z., Zhu, J., Fan, D., & Kalfadellis, P. (2018). An institutional work view toward the internationalization of emerging market firms. Journal of World Business, 53, 682–694. https://doi.org/10.1016/j.jwb.2018.03.008

Yoon, K. (1987). A reconciliation among discrete compromise situations. Journal of the Operational Research Society, 38(3), 277–286. https://doi.org/10.1057/jors.1987.44

Yoon, K., & Kim, W. (2017). The behavioral TOPSIS. Expert Systems with Applications, 89, 266–272. https://doi.org/10.1016/j.eswa.2017.07.045

Yue, X., & Qian, X. (2015). Investment environment comparison in five Central Asian countries. Asiapacific Economic Review, 02, 73–78.

Zareie, A., Sheikhahmadi, A., & Khamforoosh, K. (2018). Influence maximization in social networks based on TOPSIS. Expert Systems with Applications, 108, 96–107. https://doi.org/10.1016/j.eswa.2018.05.001

Zeng, S. Z., Chen, S. M., & Fan, K. Y. (2020a). Interval-valued intuitionistic fuzzy multiple attribute decision making based on nonlinear programming methodology and TOPSIS method. Information Sciences, 506, 424–442. https://doi.org/10.1016/j.ins.2019.08.027

Zeng, S. Z., Luo, D. D., Zhang, C. C., & Li, X. S. (2020b). A correlation-based TOPSIS method for multiple attribute decision making with single-valued neutrosophic information. International Journal of Information Technology & Decision Making, 19(01), 343–358. https://doi.org/10.1142/S0219622019500512

Zeng, S. Z., & Xiao, Y. (2018). A method based on TOPSIS and distance measures for hesitant fuzzy multiple attribute decision making. Technological and Economic Development of Economy, 24(3), 969–983. https://doi.org/10.3846/20294913.2016.1216472

Zhong, F., & Fan, S. (2016). Investment climate assessments, East Asian development and the great recession of neo-liberalism: The case of the World Bank Doing Business Report. Journal of Contemporary Asia – Pacific Studies, 30, 118–159.