| 摘要: |
| 目的 重构同城货运服务的角色分工、服务内容与服务流程，以提高同城货运平台的服务质量与效率，提升货主使用体验。方法 综合非参与式观察法、深入访谈法和问卷调查法，对使用货运平台的货主和司机两类用户的典型交互行为流程进行调研;在此基础上，应用SAPAD理论模型，对货运服务“行为-意义-对象”三个维度之间进行映射关系研究，并通过对核心意义簇的聚类推导用户对货运服务的四个核心需求，即订单确定性、交易高效性、平台信任感和服务专业感;最后，基于需求重新规划服务的分工、内容和流程，重构了同城货运的服务框架。结论 从货主、司机双方行为切入，利用定性和定量结合的方法，可以在交互复杂的服务流程中梳理核心需求。研究结果为同城货运的设计统优化提供了新的思路和方法，丰富了SAPAD模型在多用户领域的应用实践。 |
| 关键词: 同城货运平台 服务设计 SAPAD 用户行为 |
| DOI：10.19554/j.cnki.1001-3563.2023.02.020 |
| 分类号:TB472 |
| 基金项目:浙江省哲学社会科学规划课题(21NDJC038YB) |
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| Design of Intra-city Freight Service Based on SAPAD Framework |
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LU Chun-fu, ZHU Yu-qing, WU Jian-feng, YAO Ji
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(Zhejiang University of Technology, Hangzhou 310023, China)
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| Abstract: |
| The work aims to reconstruct the labor division, content and process of intra-city freight service, to improve the quality and efficiency of intra-city freight service and enrich the shippers' use experience. Non-participatory observation, questionnaire and interview methods were used to investigate the typical interactive behavior process of shipper and driver using the freight platform. Based on this, SAPAD theoretical model was applied to study the mapping relationship among the "behavior-meaning-object" of freight service. Then, through the clustering of the core meaning clusters, the four core requirements of user for intra-city freight service were deduced:order certainty, transaction efficiency, platform trust, and service professionalism. Finally, the labor division, content and process of service were re-planned based on the requirements, and the intra-city freight service framework was reconstructed. Based on the comprehensive behaviors of the shipper and the driver, qualitative and quantitative methods can be combined to sort out the core requirements in the complex service interaction process. The research results provide new ideas and methods for the optimization of the intra-city freight service design, and enrich the application practice of SAPAD in the multi-user field. |
| Key words: intra-city freight platform service design SAPAD user behavior |
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