Journal of Information Processing Systems

Korea Information Processing Society (한국정보처리학회)
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Models and Methods for the Evaluation of Automobile Manufacturing Supply Chain Coordination Degree Based on Collaborative Entropy

  • Xiao, Qiang (School of Economics and Management, Lanzhou Jiao tong University) ;
  • Wang, Hongshuang (School of Economics and Management, Lanzhou Jiao tong University)
  • Received : 2021.06.22
  • Accepted : 2022.01.24
  • Published : 2022.04.30
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Abstract

Through the analysis of the coordination mechanism of the supply chain system of China's automobile manufacturing industry, the factors affecting the supply subsystem, the manufacturing subsystem, the sales subsystem, and the consumption subsystem are sorted out, the supply chain coordination index system based on the influence factor of four subsystems is established. The evaluation models of the coordination degree in the subsystem of the supply chain, the coordination degree among the subsystems, and the comprehensive coordination degree are established by using the efficiency coefficient method and the collaborative entropy method. Experimental results verify the accuracy of the evaluation model using the empirical analysis of the collaborative evaluation index data of China's automobile manufacturing industry from 2000 to 2019. The supply chain synergy of automobile manufacturing industry was low from 2001 to 2005, and it increased to a certain extent from 2006 to 2008 with a small growth rate from 0.10 to 0.15. From 2009 to 2013, the supply chain synergy of automobile manufacturing industry increased rapidly from 0.24 to 0.49, and it also increased rapidly but fluctuated from 2014 to 2019, first rising from 0.68 to 0.84 then dropping to 0.71. These results provide reference for the development of China's automobile manufacturing supply chain system and scientific decision-making basis for the formulation of relevant policies of the automobile manufacturing industry.

Keywords

Acknowledgement

This paper are supported by the National Natural Science Foundation of China (No. 52062026) and Educational Commission of Gansu Province of China (No. 2019A-041).

References

  1. A. Awheda, M. N. A. Rahman, R. Ramli, and H. Arshad, "Impediments of collaborative relationships in automotive SMEs in Malaysia," Applied Mechanics and Materials, vol. 663, pp. 638-643, 2014. https://doi.org/10.4028/www.scientific.net/amm.663.638
  2. M. Holweg and E. K. Pil, "Theoretical perspectives on the coordination of supply chains," Journal of Operations Management, vol. 26, no. 3, pp. 389-406, 2008. https://doi.org/10.1016/j.jom.2007.08.003
  3. M. A. Villegas and D. J. Pedregal, "Supply chain decision support systems based on a novel hierarchical forecasting approach," Decision Support Systems, vol. 114, pp. 29-36, 2018. https://doi.org/10.1016/j.dss.2018.08.003
  4. Y. Hou, F. Wei, S. X. Li, Z. Huang, and A. Ashley, "Coordination and performance analysis for a three-echelon supply chain with a revenue sharing contract," International Journal of Production Research, vol. 55, no. 1, pp. 202-227, 2017. https://doi.org/10.1080/00207543.2016.1201601
  5. A. Soylu, C. Oru, M. Turkay, K. Fujita, and T. Asakura, "Synergy analysis of collaborative supply chain management in energy systems using multi-period MILP," European Journal of Operational Research, vol. 174, no. 1, pp. 387-403, 2006. https://doi.org/10.1016/j.ejor.2005.02.042
  6. L. Chen, X. Zhao, O. Tang, L. Price, S. Zhang, and W. Zhu, "Supply chain collaboration for sustainability: a literature review and future research agenda," International Journal of Production Economics, vol. 194, pp. 73-87, 2017. https://doi.org/10.1016/j.ijpe.2017.04.005
  7. C. Gimenez, V. Sierra, J. Rodon, and J. A. Rodriguez, "The role of information technology in the environmental performance of the firm: the interaction effect between information technology and environmental practices on environmental performance," Academia Revista Latinoamericana de Administracion, vol. 28, no. 2, pp. 273-291, 2015. https://doi.org/10.1108/ARLA-08-2014-0113
  8. Y. Dou, Q. Zhu, and J. Sarkis, "Evaluating green supplier development programs with a grey-analytical network process-based methodology," European Journal of Operational Research, vol. 233, no.2, pp. 420-431, 2014. https://doi.org/10.1016/j.ejor.2013.03.004
  9. D. J. Tian, K. C. Wei, J. J. Xu, and X. Ji, "The coordination evaluation models of supply chain network for chemical enterprises," Chemical Industry and Engineering Progress, vol. 35, no. 7, pp. 2285-2292, 2016.
  10. N. Labiad, Z. Beidouri, and O. Bouksour, "Evaluation of coordination contracts for a two stage supply chain under price dependent demand," International Journal of Computer Science Issues, vol. 9, no. 1, pp. 151-159, 2012.
  11. A. Xu and Y. Shang, "Cooperative quality evaluation of supply chain using structural characteristics," International Journal of Performability Engineering, vol. 16, no. 5, pp. 775-783, 2020. https://doi.org/10.23940/ijpe.20.05.p11.775783
  12. Arshinder, A. Kanda, and S. G. Deshmukh, "Coordination in supply chains: an evaluation using fuzzy logic," Production Planning & Control, vol. 18, no. 5, pp. 420-435, 2007. https://doi.org/10.1080/09537280701430994
  13. K. H. Um and S. M. Kim, "The effects of supply chain collaboration on performance and transaction cost advantage: the moderation and nonlinear effects of governance mechanisms," International Journal of Production Economics, vol. 217, pp. 97-111, 2019. https://doi.org/10.1016/j.ijpe.2018.03.025
  14. W. P. Wang, "A supply chain collaboration model based on system dynamics," Advanced Materials Research, vol. 490, pp. 1997-2001, 2012. https://doi.org/10.4028/www.scientific.net/AMR.490-495.1997
  15. N. T. M. Anh, L. Hui, V. D. Khoa, and S. Mehmood, "Relational capital and supply chain collaboration for radical and incremental innovation: an empirical study in China," Asia Pacific Journal of Marketing and Logistics, vol. 31, no. 4, pp. 1076-1094, 2019. https://doi.org/10.1108/APJML-10-2018-0423
  16. R. Grange, G. Heaslip, and C. McMullan, "Coordination to choreography: the evolution of humanitarian supply chains," Journal of Humanitarian Logistics and Supply Chain Management, vol. 10, no. 1, pp. 21-44, 2020. https://doi.org/10.1108/jhlscm-12-2018-0077
  17. B. Yan, Z. Chen, and H. Kang, "Coordination model of quality risk control of the aquatic supply chain based on principal-agent theory," Supply Chain Management, vol. 22, no. 5, pp. 393-410, 2017. https://doi.org/10.1108/SCM-10-2016-0375
  18. T. Gruchmann, S. Seuring, and K. Petljak, "Assessing the role of dynamic capabilities in local food distribution: a theory-elaboration study," Supply Chain Management, vol. 24, no. 6, pp. 767-783, 2019. https://doi.org/10.1108/scm-02-2019-0073
  19. Y. Sabri, M. H. Zarei, and C. Harland, C. (2019). Using collaborative research methodologies in humanitarian supply chains. Journal of Humanitarian Logistics and Supply Chain Management, vol. 9, no. 3, pp. 371-409, 2019. https://doi.org/10.1108/jhlscm-06-2018-0041
  20. M. Hofmann, S. Munster, and J. R. Noennig, "A theoretical framework for the evaluation of massive digital participation systems in urban planning," Journal of Geovisualization and Spatial Analysis, vol. 4, article no. 3, 2020. https://doi.org/10.1007/s41651-019-0040-3
  21. V. Kolici, A. Herrero, and F. Xhafa, "On the performance of Oracle grid engine queuing system for computing intensive applications," Journal of Information Processing Systems, vol. 10, no. 4, pp. 491-502, 2014. https://doi.org/10.3745/JIPS.01.0004