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Electronic Commerce Research

, Volume 19, Issue 4, pp 841–861 | Cite as

A two-sided matching model in the context of B2B export cross-border e-commerce

  • Yumeng Miao
  • Rong Du
  • Jin LiEmail author
  • J. Christopher Westland
Article
  • 238 Downloads

Abstract

Cross-border electronic commerce plays an increasingly key role in international trades, which has become the focus of concern in both academia and industry. However, how to better match overseas demanders and domestic suppliers is still a question for business-to-business export agent. To achieve a steady state, in this study, we apply the two-sided matching method to business-to-business export cross-border electronic commerce context based on the satisfaction of different stakeholders, i.e., sellers, buyers, platforms, and third-party service providers. The satisfaction degree is based on a series of indicators extracted from the prior literature. By incorporating both the linguistic and interval assessment information, we theoretically build an optimization model to match the two sides: overseas demanders and domestic suppliers. Then we empirically illustrate the feasibility and performance of the model through the numerical simulations. The operation mechanisms and managerial guidelines for the two-sided matching in business-to-business export cross-border e-commerce are presented. Our study makes contributions in both theory and practice.

Keywords

Cross-border e-commerce Two-sided matching Overseas demander Domestic supplier Business-to-business export 

Notes

Funding

This study was financially supported by National Natural Science Foundation of China (71771184), China Postdoctoral Science Foundation (2019M650035), Chinese Fundamental Research Funds for Central Universities (JB180602), and China Scholarship Council.

Compliance with ethical standards

Conflict of interest

The authors state that they have no conflict of interest.

References

  1. 1.
    Azevedo, E. M., & Leshno, J. D. (2016). A supply and demand framework for two-sided matching markets. Journal of Political Economy,124(5), 1235–1268.Google Scholar
  2. 2.
    Benton, W. C., & Maloni, M. (2005). The influence of power driven buyer/seller relationships on supply chain satisfaction. Journal of Operations Management,23(1), 1–22.Google Scholar
  3. 3.
    Caniëls, M. C., Vos, F. G., Schiele, H., & Pulles, N. J. (2018). The effects of balanced and asymmetric dependence on supplier satisfaction: Identifying positive effects of dependency. Journal of Purchasing and Supply Management,24, 343–351.Google Scholar
  4. 4.
    Chavez, R., Yu, W., Feng, M., & Wiengarten, F. (2016). The effect of customer-centric green supply chain management on operational performance and customer satisfaction. Business Strategy and the Environment,25(3), 205–220.Google Scholar
  5. 5.
    Chen, J., & Song, K. (2013). Two-sided matching in the loan market. International Journal of Industrial Organization,31(2), 145–152.Google Scholar
  6. 6.
    Chen, X., Li, Z., Fan, Z. P., & Zhang, X. (2016). Matching demanders and suppliers in knowledge service: A method based on fuzzy axiomatic design. Information Sciences,346–347, 130–145.Google Scholar
  7. 7.
    Cronin, J. J., Jr., & Taylor, S. A. (1992). Measuring service quality: A reexamination and extension. Journal of Marketing,56(3), 55–68.Google Scholar
  8. 8.
    Cui, Y., Mou, J., Cohen, J., & Liu, Y. (2019). Understanding information system success model and valence framework in sellers’ acceptance of cross-border e-commerce: A sequential multi-method approach. Electronic Commerce Research.  https://doi.org/10.1007/s10660-019-09331-0.Google Scholar
  9. 9.
    Dai, N., & Nahata, R. (2016). Cultural differences and cross-border venture capital syndication. Journal of International Business Studies,47(2), 140–169.Google Scholar
  10. 10.
    Deng, Z., & Wang, Z. (2016). Early-mover advantages at cross-border business-to-business e-commerce portals. Journal of Business Research,69(12), 6002–6011.Google Scholar
  11. 11.
    Echenique, F. (2008). What matchings can be stable? The testable implications of matching theory. Mathematics of Operations Research,33(3), 757–768.Google Scholar
  12. 12.
    Ecommerce WIKI. https://www.ecommercewiki.org/Cross-border_Ecommerce. Accessed July 12, 2018.
  13. 13.
    Electronic Commerce Research Center. (2018). 2017 China export cross-border e-commerce development report. http://www.100ec.cn/zt/17zgfz/. Accessed July 12, 2018.
  14. 14.
    Gomez-Herrera, E., Martens, B., & Turlea, G. (2014). The drivers and impediments for cross-border e-commerce in the EU. Information Economics and Policy,28, 83–96.Google Scholar
  15. 15.
    Guo, Y., Bao, Y., Stuart, B. J., & Le-Nguyen, K. (2018). To sell or not to sell: Exploring sellers’ trust and risk of chargeback fraud in cross-border electronic commerce. Information Systems Journal,28(2), 359–383.Google Scholar
  16. 16.
    Guo, Y., Le-Nguyen, K., Jia, Q., & Li, G. (2015). Seller-buyer trust in cross-border e-commerce: A conceptual model. In Proceeding of the 21st Americas Conference on Information Systems (AMCIS). Puerto Rico.Google Scholar
  17. 17.
    Huang, S., & Chang, Y. (2017). Factors that impact consumers’ intention to shop on foreign online stores. In Proceeding of the 50th Hawaii International Conference on System Sciences (HICSS), Hawaii.Google Scholar
  18. 18.
    Janssen, M., & Verbraeck, A. (2008). Comparing the strengths and weaknesses of internet-based matching mechanisms for the transport market. Transportation Research Part E Logistics & Transportation Review,44(3), 475–490.Google Scholar
  19. 19.
    Jiang, Z. Z., Sheng, Y., Fan, Z. P., & Yuan, Y. (2008). Research on multi-objective decision model for bipartite matching with incomplete information on attribute weights. Operational Research and Management Science,17(4), 138–142.Google Scholar
  20. 20.
    Keskinocak, P., Goodwin, R., Wu, F., Akkiraju, R., & Murthy, S. (2001). Decision support for managing an electronic supply chain. Electronic Commerce Research,1(1–2), 15–31.Google Scholar
  21. 21.
    Kim, T. Y., Dekker, R., & Heij, C. (2017). Cross-border electronic commerce: Distance effects and express delivery in European Union markets. International Journal of Electronic Commerce,21(2), 184–218.Google Scholar
  22. 22.
    Kshetri, N., Bebenroth, R., Williamson, N. C., & Sharma, R. S. (2014). Cross-national heterogeneity in e-retail spending: A longitudinal analysis of economic, technological and political forces. Electronic Commerce Research,14(4), 585–609.Google Scholar
  23. 23.
    Lai, J. Y., & Yang, C. C. (2009). Effects of employees’ perceived dependability on success of enterprise applications in e-business. Industrial Marketing Management,38(3), 263–274.Google Scholar
  24. 24.
    Lin, J. A., Li, Y. E., & Lee, S. Y. (2018). Dysfunctional customer behavior in cross-border e-commerce: A justice-affect-behavior model. Journal of Electronic Commerce Research,19(1), 36–54.Google Scholar
  25. 25.
    Lin, Y., Wang, Y. M., & Chen, S. Q. (2017). Hesitant fuzzy multiattribute matching decision making based on regret theory with uncertain weights. International Journal of Fuzzy Systems,19(4), 955–966.Google Scholar
  26. 26.
    Liu, S., Chan, F. T. S., & Ran, W. (2013). Multi-attribute group decision-making with multi-granularity linguistic assessment information: An improved approach based on deviation and TOPSIS. Applied Mathematical Modelling,37(24), 10129–10140.Google Scholar
  27. 27.
    Liu, Y., & Li, K. W. (2017). A two-sided matching decision method for supply and demand of technological knowledge. Journal of Knowledge Management,21(3), 592–606.Google Scholar
  28. 28.
    Ma, S., Chai, Y., & Zhang, H. (2018). Rise of cross-border e-commerce exports in China. China & World Economy,26(3), 63–87.Google Scholar
  29. 29.
    Ministry of Finance of the People’s Republic of China. (2013). The tax policy announcement for export retails through cross-border e-commerce. Accessed through http://www.mof.gov.cn/ on December 30, 2013.
  30. 30.
    Mou, J., Cohen, J., Dou, Y. & Zhang, B. (2017). Predicted buyers’ repurchase intentions in cross-border e-commerce: A valence framework perspective. In Proceeding of the 25th European Conference on Information Systems (ECIS). Guimarães, Portugal.Google Scholar
  31. 31.
    Mwangi, A. W., & Wanjau, K. (2018). Influence of perceived service quality on consumer satisfaction amongst dairy milk processors in Kenya. International Journal of Research in Business and Social Science,7(4), 44–57.Google Scholar
  32. 32.
    National Business Daily. (2018). http://www.nbd.com.cn/articles/2018-06-08/1224499.html. Accessed July 12, 2018.
  33. 33.
    Nyaga, G. N., Whipple, J. M., & Lynch, D. F. (2010). Examining supply chain relationships: Do buyer and supplier perspectives on collaborative relationships differ? Journal of Operations Management,28(2), 101–114.Google Scholar
  34. 34.
    Pei, Y., Wu, K., & Dai, L. (2016). An empirical research on the evaluation system of cross-border e-commerce. In Proceeding of the 15th Wuhan International Conference on E-Business (WHICEB). Wuhan.Google Scholar
  35. 35.
    Roth, A. E. (1985). Common and conflicting interests in two-sided matching markets. European Economic Review,27(1), 75–96.Google Scholar
  36. 36.
    Sarne, D., & Kraus, S. (2008). Managing parallel inquiries in agents’ two-sided search. Artificial Intelligence,172(4–5), 541–569.Google Scholar
  37. 37.
    Sørensen, M. (2007). How smart is smart money? A two-sided matching model of venture capital. The Journal of Finance,62(6), 2725–2762.Google Scholar
  38. 38.
    Sullivan, P., Bonn, M., Bhardwaj, V., & DuPont, A. (2012). Mexican national cross-border shopping: Exploration of retail tourism. Journal of Retailing & Consumer Services,19(6), 596–604.Google Scholar
  39. 39.
    Wang, Y., Wang, Y., & Lee, S. H. (2017). The effect of cross-border e-commerce on China’s international trade: An empirical study based on transaction cost analysis. Sustainability,9(11), 2028.Google Scholar
  40. 40.
    Wang, Q., Xu, Z., Cui, X., & Ouyang, C. (2017). Does a big Duchenne smile really matter on e-commerce websites? An eye-tracking study in China. Electronic Commerce Research,17, 609–626.Google Scholar
  41. 41.
    Xinhua Silk Road Information Service. (2018). http://silkroad.news.cn/2018/0402/90556.shtml. Accessed July 12, 2018.
  42. 42.
    Yeung, R., & Yee, W. (2012). A profile of the mainland Chinese cross-border shoppers: Cluster and discriminant analysis. Tourism Management Perspectives,4(4), 106–112.Google Scholar
  43. 43.
    Zhang, Z., & Guo, C. H. (2011). A hybrid multiple attributes two-sided matching decision making method with incomplete weight information. In Proceeding of the International Conference on Brain Informatics. Berlin, Heidelberg.Google Scholar
  44. 44.
    Zheng, X. X., Li, D. F., Wang, Y., & Liu, J. C. (2016). Research on two-sided matching model based on knowledge service of cross-border e-commerce supply chain. Modern Information,11(43–49), 54.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Yumeng Miao
    • 1
  • Rong Du
    • 1
  • Jin Li
    • 2
    Email author
  • J. Christopher Westland
    • 3
  1. 1.School of Economics and ManagementXidian UniversityXi’anChina
  2. 2.School of ManagementXi’an Jiaotong UniversityXi’anChina
  3. 3.Department of Information & Decision SciencesUniversity of Illinois – ChicagoChicagoUSA

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