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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2020  >  20(1): 192-203
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. doi: 10.19818/j.cnki.1671-1637.2020.01.016
Citation: 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. doi: 10.19818/j.cnki.1671-1637.2020.01.016
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Optimization of differentiated service level for multi-level customers

doi: 10.19818/j.cnki.1671-1637.2020.01.016
  • 1.

    School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, Sichuan, China

  • 2.

    Department of Road Traffic Management, Sichuan Police CollegeLuzhou 646000, Sichuan, China

  • 3.

    National United Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University, Chengdu 610031, Sichuan, China

More Information
  • Author Bio:

    XIEHAN Xun(1991-), female, lecturer, PhD, hldwxhx@163.com

  • Corresponding author: ZHANG Jin(1963-), male, professor, PhD, zhjswjtu@swjtu.edu.cn
  • Received Date: 2019-06-05
  • Publish Date: 2020-02-25
    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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