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Customer Evaluation-Based Automobile After-Sale Service Multi-value-Chain Collaborative Mechanism Verification

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Human Centered Computing (HCC 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11956))

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Abstract

In the automotive after-sales service cycle, according to the historical information of the service received by the customer during the period of warranty services of repair, replacement and refund, the customer’s willingness to choose the out-of-warranty service is evaluated, and differentiated collaborative services are provided, which can effectively improve the service quality. This paper proposes a collaborative mechanism design and verification method of automobile after-sales service multi-value-chain based on customer evaluation. First, it studies the composition of the service value chain during the warranty period, outside of the warranty period, and the insurance service, explores the source of income and gain factors of each value process to discover the appropriate service business and proving the ability of customer assessment for value creation in the value process. Then, establish a colored Petri Net model for each service value chain, the resources required for after-sales service are mapped to Token in Place and Place and the income is mapped to Transition, which can simulate the gain process of a single service-value-chain. Finally, based on the customer evaluation level, the design provides a differentiated automobile after-sales collaborative service multi-value-chain mechanism, generates the random customer sequence. And the gain effect of multi-value-chain in collaborative status is simulated and operated on the CPN Tools which is a running platform based on colored Petri Net. The results show that the above-mentioned mechanism makes the expenses of important customers relatively reduced, and the income of service providers and insurers increased which is conducive to maintain the ability of auto service providers to extend after-sales service. In addition, it provides a quantitative basis for collaborative optimization of service multi-value-chain.

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Acknowledgment

The authors would like to thank the anonymous referees for their valuable comments and helpful suggestions. This paper is supported by The National Key Research and Development Program of China (2017YFB1400902).

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Correspondence to Changyou Zhang .

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Liu, D., Bo, W., Wu, C., Yang, H., Zhang, C. (2019). Customer Evaluation-Based Automobile After-Sale Service Multi-value-Chain Collaborative Mechanism Verification. In: Milošević, D., Tang, Y., Zu, Q. (eds) Human Centered Computing. HCC 2019. Lecture Notes in Computer Science(), vol 11956. Springer, Cham. https://doi.org/10.1007/978-3-030-37429-7_23

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  • DOI: https://doi.org/10.1007/978-3-030-37429-7_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37428-0

  • Online ISBN: 978-3-030-37429-7

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