首页> 外文期刊>International Journal of Production Research >Social and environmental risk management in resilient supply chains: A periodical study by the Grey-Verhulst model
【24h】

Social and environmental risk management in resilient supply chains: A periodical study by the Grey-Verhulst model

机译:弹性供应链中的社会和环境风险管理:Grey-Verhulst模型的定期研究

获取原文
获取原文并翻译 | 示例
       

摘要

As sustainability and allied concerns are at present gaining greater than before attention amongst stakeholders, enterprises are enforced to consider social and environmental risk assessments along with conventional economic risk assessments. Hence to advance sustainable competitive advantages, the property of resilience is becoming a success factor for enterprises. Resilience is the property of enterprises or their supply chains to resume operations after disruptions and to regain its sustainable competitive advantages quickly and effectively. This study essentially focuses on identifying drivers of social and environmental risk management (SERM) in resilient supply chains and to acknowledge the importance of these drivers towards the implementation of SERM practices of enterprises. Representative case studies of three electronics manufacturing firms were also considered in this research to gain practical insights. Periodical data analysis has been piloted for the collected datasets from these companies. Since the sequences of the collected data show saturated sigmoidal tendencies, the Verhulst model fits best with the data sequences. A Grey-Verhulst model has been implemented in this research and was practically tested for case firms to exemplify the data sequences of prediction and to effectually improve the SERM performances of firms.
机译:当前,由于可持续性和相关问题的关注度越来越高,而利益相关者的关注度也越来越高,因此企业被迫考虑社会和环境风险评估以及常规经济风险评估。因此,为了提高可持续的竞争优势,弹性属性已成为企业成功的因素。复原力是企业或其供应链在中断后恢复运营并快速有效地恢复其可持续竞争优势的财产。这项研究主要着眼于确定弹性供应链中的社会和环境风险管理(SERM)驱动因素,并认识到这些驱动因素对于企业实施SERM做法的重要性。本研究还考虑了三个电子制造公司的代表性案例研究,以获取实际见解。已针对从这些公司收集的数据集试用了定期数据分析。由于收集的数据序列显示出饱和的S形趋势,因此Verhulst模型最适合数据序列。 Grey-Verhulst模型已在此研究中实施,并已针对案例公司进行了实际测试,以例证预测的数据序列并有效改善公司的SERM绩效。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号