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基于DEMATEL-ISM与ANP模型的半导体供应链弹性影响因素研究
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Abstract:
当前关于半导体供应链弹性影响因素的研究十分有限，针对这一现状，本文采用了基于DEMATEL-ISM与ANP模型的综合性方法对半导体供应链弹性影响因素进行研究。首先，本文筛选出包括准备能力、响应能力、恢复能力和学习能力在内的4个半导体供应链弹性影响因素一级指标，同时引入15个相应的二级指标，以此构建半导体供应链弹性评价体系。最后，结合实证研究，以某半导体上市企业为例，运用DEMATEL-ISM方法，研究半导体行业中影响供应链弹性的各因素之间的关系，并使用ANP方法对各二级指标进行权重评定。通过这一系列分析，本文成功识别出影响该企业供应链弹性最根本的影响因素及关键指标，为半导体企业在增强供应链弹性方面提供理论指导与实践参考。
The current research on the influencing factors of semiconductor supply chain resilience is relatively limited. To response to this issue, this study employs a comprehensive approach based on the DEMATEL-ISM and ANP models. Initially, four primary indicators of semiconductor supply chain resilience are identified, including preparedness, responsiveness, recovery, and learning capabilities, along with 15 corresponding secondary indicators to construct an evaluation system for semiconductor supply chain resilience. Through empirical research, taking a semiconductor company as the research object, the DEMATEL-ISM method is used to analyze the relationships among the influencing factors of semiconductor supply chain resilience. Subsequently, the ANP method is applied to evaluate the weights of the secondary indicators, identifying the most fundamental influencing factors and key indicators affecting the supply chain resilience of the company, which provides theoretical guidance and practical references for semiconductor companies to enhance their supply chain resilience.
| [1] | 吴胜. 中国国内半导体集成电路行业现状及未来供应链发展趋势[J]. 中国采购发展报告, 2012(00): 410-416. |
| [2] | Kochan, C.G. and Nowicki, D.R. (2018) Supply Chain Resilience: A Systematic Literature Review and Typological Framework. International Journal of Physical Distribution & Logistics Management, 48, 842-865. https://doi.org/10.1108/ijpdlm-02-2017-0099 |
| [3] | Xiong, W., Wu, D.D. and Yeung, J.H.Y. (2024) Semiconductor Supply Chain Resilience and Disruption: Insights, Mitigation, and Future Directions. International Journal of Production Research. https://doi.org/10.1080/00207543.2024.2387074 |
| [4] | Moktadir, M.A. and Ren, J. (2024) Global Semiconductor Supply Chain Resilience Challenges and Mitigation Strategies: A Novel Integrated Decomposed Fuzzy Set Delphi, WINGS and QFD Model. International Journal of Production Economics, 273, Article ID: 109280. https://doi.org/10.1016/j.ijpe.2024.109280 |
| [5] | Achter, S., Lorscheid, I., Hauke, J., Meyer, M., Meyer-Riehl, D., Ponsignon, T., et al. (2017) On Agent-Based Modeling in Semiconductor Supply Chain Planning. 2017 Winter Simulation Conference (WSC), Las Vegas, 3-6 December 2017, 3507-3518. https://doi.org/10.1109/wsc.2017.8248065 |
| [6] | Fu, W., Jing, S., Liu, Q. and Zhang, H. (2023) Resilient Supply Chain Framework for Semiconductor Distribution and an Empirical Study of Demand Risk Inference. Sustainability, 15, Article No. 7382. https://doi.org/10.3390/su15097382 |
| [7] | Lin, C., Kao, S. and Chen, L. (2011) A Proactive Operational Framework for Business Continuity in the Semiconductor Industry. Quality and Reliability Engineering International, 28, 307-320. https://doi.org/10.1002/qre.1246 |
| [8] | Ejdys, J. and Szpilko, D. (2023) How to Ensure the Resilience of Semiconductor Supply Chains in the European Union? Polish Journal of Management Studies, 28, 101-122. https://doi.org/10.17512/pjms.2023.28.1.06 |
| [9] | Kumar, D., Soni, G., Mangla, S.K., Liao, J., Rathore, A.P.S. and Kazancoglu, Y. (2024) Integrating Resilience and Reliability in Semiconductor Supply Chains during Disruptions. International Journal of Production Economics, 276, Article ID: 109376. https://doi.org/10.1016/j.ijpe.2024.109376 |
| [10] | Ishak, S., Shaharudin, M.R., Salim, N.A.M., Zainoddin, A.I. and Deng, Z. (2023) The Effect of Supply Chain Adaptive Strategies during the COVID-19 Pandemic on Firm Performance in Malaysia's Semiconductor Industries. Global Journal of Flexible Systems Management, 24, 439-458. https://doi.org/10.1007/s40171-023-00347-y |
| [11] | Aylor, B., Datta, B., Defauw, M., et al. (2020) Designing Resilience into Global Supply Chains. Boston Consulting Group. |
