| 全渠道服务商在线上自助服务技术背景下的定价策略研究 |
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| 引用本文： | 郑夏冰,徐航,李雪,杨锋. 全渠道服务商在线上自助服务技术背景下的定价策略研究[J]. 运筹与管理, 2022, 31(7): 179-185. DOI: 10.12005/orms.2022.0234 |
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| 作者姓名： | 郑夏冰 徐航 李雪 杨锋 |
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| 作者单位： | 中国科学技术大学 管理学院,安徽 合肥 230026 |
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| 基金项目： | 国家自然科学基金资助项目(71701195,71631006,71991464,71921001) |
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| 摘 要： | 在线上自助服务技术兴起的背景下,研究餐饮业服务商整合全渠道的定价策略。分析归纳了三种提供服务的渠道(线下取号排队、线上取号排队、线上预定);利用排队论以及依据消费者效用对服务系统进行理论建模,并结合数值分析,为服务商如何应对不同的消费者与市场环境指明了方向。研究发现:(1)给出了三种服务渠道的最优定价模型表示,并结合市场情况分析不同的定价策略,如在服务高峰期可以采取歧视定价策略;(2)指明了线上取号与线上预定两种渠道不宜同时提供,并给出了最优的线上预定的预留容量比例,对商家设计渠道具有指导意义;(3)发现了不管线下消费者比例如何,服务商营收曲线必定经过同一点,对服务商采取措施引流具有启发意义。本文对服务商全渠道理论建模具有启发意义。
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| 关 键 词： | 线上服务技术 定价策略 线下取号排队 线上预定 排队论 |
Research on Pricing Strategies of Omni-channel Service Providers under the Background of Online Self-service Technology |
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| ZHENG Xia-bing,XU Hang,LI Xue,YANG Feng. Research on Pricing Strategies of Omni-channel Service Providers under the Background of Online Self-service Technology[J]. Operations Research and Management Science, 2022, 31(7): 179-185. DOI: 10.12005/orms.2022.0234 |
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| Authors: | ZHENG Xia-bing XU Hang LI Xue YANG Feng |
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| Affiliation: | School of Management, University of Science and Technology of China, Hefei 230026, China |
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| Abstract: | In this paper, we study the omni-channel pricing strategies for the service providers using online self-service technology. We summarize three types of channels for providing services (offline queuing, online queuing, and online booking). Using the queuing theory, we set a theoretical model of the service system based on consumers’ utilities. We also examine the way in which service providers respond to different consumers and markets through the combination of numerical analysis. The results show each optimal pricing model for the three service channels and the pricing strategies in different market conditions. For example, discriminatory pricing strategies are recommended during peak periods of service. The results also indicate that online queuing and online booking should not be provided at the same time. In addition, we propose the optimal reserve capacity ratio of online booking, which is important for service providers. We also find that the curves of the service providers’ revenues will pass through a same point no matter the ratio of offline consumers. This paper is instructive for omni-channel theoretical modeling of service providers. |
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| Keywords: | online self-service technology pricing strategies offline queuing online booking queuing theory |
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