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面向多级别顾客的差异化服务水平优化
引用本文:韩珣,张锦.面向多级别顾客的差异化服务水平优化[J].交通运输工程学报,2020,20(1):192-203.
作者姓名:韩珣  张锦
作者单位:1.西南交通大学交通运输与物流学院, 四川 成都 6100312.四川警察学院道路交通管理系, 四川 泸州 6460003.西南交通大学综合交通运输智能化国家地方联合工程实验室, 四川 成都 610031
基金项目:国家自然科学基金;中央高校基本科研业务费专项科技创新项目;国家社会科学基金
摘    要:基于顾客满意度受到当前供给各要素和以往服务体验共同影响的前提, 建立了参考效应下考虑距离、服务水平和价格等多因素影响的顾客效用函数; 对比顾客在不同企业获得的效用, 引入概率模型刻画顾客选择行为, 提出了服务水平与单位服务成本的关联函数, 构建利润最大化的服务水平优化模型并求解; 以具体商圈中自提服务水平为例, 对比分析了服务水平敏感性系数和竞争企业策略对优化结果的影响。研究结果表明: 敏感性系数从0.2变化为1.0时, 目标企业提供高服务水平带来需求覆盖率增长7.2%, 总利润提高10.4%;当竞争企业采取0.2的服务水平策略和1.2的价格策略时, 目标企业提供高于竞争企业0.39的服务水平吸引顾客, 并通过高价提高单位收益; 当竞争企业采取0.8的服务水平策略和1.8的价格策略时, 目标企业服务水平从0.59上调至0.63以应对竞争, 同时维持低价以保留部分价格敏感的客源; 当竞争企业采取0.2的服务水平策略和1.8的价格策略时, 目标企业通过提供高于竞争者0.47的服务水平提高市场覆盖率, 通过相近的价格保证利润空间; 当竞争企业采取0.8的服务水平策略和1.2的价格策略时, 目标企业提供低服务水平和价格以控制成本, 维持市场份额。 

关 键 词:物流工程    末端配送    自提服务    概率模型    差异化策略    顾客选择    参考效应    服务水平
收稿时间:2019-06-05

Optimization of differentiated service level for multi-level customers
HAN Xun,ZHANG Jin.Optimization of differentiated service level for multi-level customers[J].Journal of Traffic and Transportation Engineering,2020,20(1):192-203.
Authors:HAN Xun  ZHANG Jin
Affiliation:1.School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, Sichuan, China2.Department of Road Traffic Management, Sichuan Police CollegeLuzhou 646000, Sichuan, China3.National United Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University, Chengdu 610031, Sichuan, China
Abstract:Based on the premise that satisfaction degrees of customers were affected by the current supply factors and the past service experience, a customer utility function was set up considering the effects of multiple factors such as distance, service level and price under the reference effect. Comparing the utility of customers in different companies, a probability model was introduced to characterize customers' selection behaviors. The correlation function between service level and unit service cost was proposed, and the service level optimization model of maximizing profit was constructed and solved. Taking the pickup service level in a specific business circle as an example, the impacts of sensitivity coefficient for service level and the competing company strategy on the optimization results were compared and analyzed. Research result shows that when the sensitivity coefficient changes from 0.2 to 1.0, a high service level provided by the target company leads to a 7.2% increase in demand coverage and a 10.4% increase in total profit. When the competing company adopts a service level strategy of 0.2 and a price strategy of 1.2, the target company provides a service level of 0.39 higher than the competing company to attract customers, and increases unit revenue through high prices. When the competitor company adopts a service level strategy of 0.8 and a price strategy of 1.8, the target company rises the service level from 0.59 to 0.63 to cope with competition, and maintains low price to retain some price-sensitive customers. When the competitor company adopts a service level strategy of 0.2 and a price strategy of 1.8, the target company improves market coverage by providing a service level of 0.47 higher than that of the competitor, and guarantees profit margin by a quite similar price. When the competitor company adopts a service level strategy of 0.8 and a price strategy of 1.2, the target company provides relatively low service level and price to control cost and maintain market share. 
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