摘要
电动汽车租赁行业迅速发展。为满足消费者和企业的综合需求,研究了面向电动汽车租赁的多目标服务组合优化设计方法。借助模糊理论确定各服务项权重,引入失望理论描述顾客的欣喜与失望感知以计算感知绩效,建立方案成本、相容度、市场竞争指数的计算方法,最终提出顾客感知绩效最大、成本最低、方案相容最优、市场竞争力最大的电动汽车租赁多目标服务组合优化设计模型。通过一种面向多阶段的多目标权重确定法对不同阶段的多目标决策设定权重。最后,通过实际项目案例对模型进行有效性验证,针对推广市场的不同阶段分别制定服务组合套餐,目标优化结果显著,为电动汽车租赁企业在服务设计方面提供了科学有效的决策方法。
The electric vehicle lease industry has developed rapidly.In order to meet the comprehensive needs of both consumers and companies,a multi-objective service portfolio optimization design method for the electric vehicle lease is researched.The fuzzy theory method is used to determine the weight of each service item.The disappointment theory is applied to describe the customer’s delight and disappointment perception in order to calculate customer perceived performance.The calculation methods for program cost,compatibility,and market competition index are also established.A multi-objective service portfolio optimization design model of electric vehicle lease with the highest customer perceived performance,the lowest cost,the best program compatibility,and the strongest market competitiveness is finally proposed.A method for determining weights of multi-objective function is designed to set weights for multi-objective decision at different stages.Finally,through an actual case,the validity of the model is verified,which formulates the service portfolio for different stages,the target optimization results are significant,providing a scientific and effective decision-making method for the service design of electric vehicle lease companies.
作者
李奇
苗瑞
张洁
江志斌
付圆
LI Qi;MIAO Rui;ZHANG Jie;JIANG Zhibin;FU Yuan(School of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai 200240,China;College of Mechanical Engineering,Donghua University,Shanghai 201620,China;Shanghai International Automobile City New Energy Vehicle Operation Service Co.,Ltd.Shanghai 201805,China)
出处
《工业工程》
北大核心
2019年第4期101-108,共8页
Industrial Engineering Journal
基金
国家自然科学基金资助项目(51435009)
关键词
服务组合设计
电动汽车租赁
多目标优化
顾客感知绩效
service portfolio design
electric vehicle lease
multi-objective optimization
customer perceived utility
