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Research on Site Selection of Low Carbon Distribution Centers Under “New Retail”

  • Yong WangEmail author
  • Pei-lin Zhang
  • Qian Lu
  • Daniel Tesfamariam Semere
  • Xin Li
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1126)

Abstract

The “Internet +” era, the new retail model will lead the future of business trends. Combining with the characteristics of the development of the new retail industry, from the perspective of carbon emissions, we will focus on the analysis of carbon emission costs and the impact of adding businesses to enterprises, governments or the society. According to the scholar’s decision on the location of distribution center, it mainly involves the construction cost of distribution center and the increase of carbon emission cost model for comparative analysis. By comparing the total cost of social, commercial and government, and provide a basis for positioning decisions.

Keywords

New retail Low-carbon Distribution center location Sustainability 

Notes

Acknowledgment

This project is supported by Key Projects of CAST (China Association of Science and Technology) Project (2018CASTQNJL33); Fundamental Research Funds for the Central Universities (2019-JL-008); MOE Project of Humanities and Social Sciences (14YJCZH154); WTBU Academic Team (XSTD2015004).

References

  1. 1.
    Lin, Z., Xi, C.: Logistics development and change in the new retail Era. Logist. Technol. Appl. (6), 70–77 (2017). (in Chinese)Google Scholar
  2. 2.
    Shen, X.: Research on development route of logistics industry in new retail era. Mod. Commer. Ind. (6), 21–22 (2017). (in Chinese)Google Scholar
  3. 3.
    Zhao, P., Liu, B., Xu, L., Wan, D.: Location optimization of multidistribution centers based on low-carbon constraints. Discret. Dyn. Nat. Soc. 2013, 1–6 (2013). Article ID 427691Google Scholar
  4. 4.
    Liu, B., Wu, Q., Wang, F.: Regional optimization of new straw power plants with greenhouse gas emissions reduction goals: a comparison of different logistics modes. J. Clean. Prod. 161, 871–880 (2017)CrossRefGoogle Scholar
  5. 5.
    Jing, W., Zhongqin, M.: Selection of multi-distribution center location based on low carbon. Revista de la Facultad de Ingeniería U.C.V. 31(7), 11–22 (2016)Google Scholar
  6. 6.
    Zhao, P., Yu, H., Wang, Z., Xu, L.: Fuzzy evaluation of low carbon development levels for logistic enterprises in China. J. Ind. Eng. Manag. 8(5), 1698–1710 (2015)Google Scholar
  7. 7.
    Li, Y., Liu, X., Chen, Y.: Selection of logistics center location using axiomatic fuzzy set and TOPSIS methodology in logistics management. Expert Syst. Appl. 38(6), 7901–7908 (2011)CrossRefGoogle Scholar
  8. 8.
    Badri, M.A., Davis, D.L., Davis, D.: Decision support models for the location of firms in industrial sites. Int. J. Oper. Prod. Manag. 15(1), 50–62 (1995)CrossRefGoogle Scholar
  9. 9.
    Hoffman, J.J., Schniederjans, M.: A two-stage model for structuring global facility site selection decisions: the case of brewing industry. Facilities 14(4), 79–96 (1996)Google Scholar
  10. 10.
    Bozarth, C.C., Warsing, D.P., Flynn, B.B., Flynn, E.J.: The impact of supply chain complexity on manufacturing plant performance. J. Oper. Manag. 27(1), 78–93 (2009)CrossRefGoogle Scholar
  11. 11.
    Bartelsman, E., Haltiwanger, J., Scarpetta, S.: Cross-Country differences in productivity: the role of allocation and selection. Am. Econ. Rev. 103(1), 305–334 (2013)CrossRefGoogle Scholar
  12. 12.
    MacCormack, A., Newman III, L., Rosenfield, D.: The new dynamics of global manufacturing site selection. Sloan Manag. Rev. 7, 69–79 (1994)Google Scholar
  13. 13.
    Vidal, C.J., Goetschalckx, M.: Modeling the affect of uncertainties on global logistics systems. J. Bus. Logist. 21(1), 95–120 (2000)Google Scholar
  14. 14.
    Dogan, I.: Analysis of facility location model using Bayesian networks. Expert. Syst. Appl.: Int. J. 39, 1092–1104 (2012)CrossRefGoogle Scholar
  15. 15.
    Zhu, H.: Logistics distribution center site selection based on domain mean value optimization PSO algorithm. Rev. Téc. Ing. Univ. Zulia 39(5), 155–161 (2016)Google Scholar
  16. 16.
    Liu, X., Guo, X., Zhao, X.: Study on logistics center site selection of Jilin Province. J. Softw. 7(8), 1799–1806 (2012)Google Scholar
  17. 17.
    Faisal, H., Usman, S., Zahid, S.M.: In what ways smart cities will get assistance from internet of things (IOT). Int. J. Educ. Manag. Eng. (IJEME) 8(2), 41–47 (2018)CrossRefGoogle Scholar
  18. 18.
    Wang, Y., Zhang, P., Lu, Q., Semere, D.T., Du, W.: Supplier measurement of fresh supply chain in sustainable environment. EKOLOJI 28(107), 1995–2004 (2019)Google Scholar
  19. 19.
    Aggarwal, A., Verma, R., Singh, A.: An efficient approach for resource allocations using hybrid scheduling and optimization in distributed system. Int. J. Educ. Manag. Eng. (IJEME) 8(3), 33–42 (2018)CrossRefGoogle Scholar
  20. 20.
    Tao, Y.: Logistics network planning of multiple transportation modes under low carbon economy, pp. 16–20. Shanghai Jiao Tong University, Shanghai (2011). (in Chinese)Google Scholar
  21. 21.
    Wang, Y., Deng, X.: Empirical study on performance evaluation of agricultural product supply chain based on factor analysis. China Bus. Mark. 5(3), 10–16 (2015). (in Chinese)Google Scholar
  22. 22.
    Khan, S.: Cloud computing: issues and risks of embracing the cloud in a business environment. Int. J. Educ. Manag. Eng. (IJEME) 9(4), 44–56 (2019)Google Scholar
  23. 23.
    Kajol, R., Akshay, K.K., Keerthan Kumar, T.G.: Fresh automated agricultural field analysis and monitoring system using IOT. Int. J. Inf. Eng. Electron. Bus. (IJIEEB) 10(2), 17–24 (2018)Google Scholar
  24. 24.
    Datta, L.: Efficient Round Robin scheduling algorithm with dynamic time slice. Int. J. Educ. Manag. Eng. (IJEME) 5(2), 10–19 (2015)CrossRefGoogle Scholar

Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Yong Wang
    • 1
    • 2
    Email author
  • Pei-lin Zhang
    • 1
  • Qian Lu
    • 3
  • Daniel Tesfamariam Semere
    • 2
  • Xin Li
    • 4
  1. 1.School of TransportationWuhan University of TechnologyWuhanChina
  2. 2.Department of Production EngineeringKTH Royal Institute of TechnologyStockholmSweden
  3. 3.Department of PlanningPuren HospitalWuhanChina
  4. 4.School of LogisticsWuhan Technology and Business UniversityWuhanChina

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