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[经济学] 影响大众运输使用的因素 服务 [推广有奖]

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kedemingshi 在职认证  发表于 2022-3-5 21:19:50 来自手机 |AI写论文

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摘要翻译:
本研究的目的是了解寄件人如何为不同的产品选择航运服务,考虑到在物流市场中既有新兴的大众航运(CS)也有传统的承运人。利用从美国调查中收集的数据,随机效用最大化(RUM)和随机后悔最小化(RRM)模型被用来揭示影响寄件人决策多样性的因素。运输成本,以及其他实时服务,如信使声誉、跟踪信息、电子通知和定制的送货时间和地点,已被发现对寄件人的选择有显著影响。有趣的是,潜在的寄件人愿意支付更多的费用来通过CS服务运送食品、饮料和药品等杂货物品。此外,实时服务的弹性很低,这意味着这些服务的微小变化将导致发送者行为的变化。最后,使用数据科学技术评估了RUM和RRM模型的性能,发现具有相似的精确度。本文的研究结果将有助于物流企业解决潜在的市场细分问题,准备满足寄件人期望的服务配置,并制定有效的业务运营策略。
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英文标题:
《Influencing factors that determine the usage of the crowd-shipping
  services》
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作者:
Tho V. Le and Satish V. Ukkusuri
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最新提交年份:
2019
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分类信息:

一级分类:Economics        经济学
二级分类:General Economics        一般经济学
分类描述:General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
--
一级分类:Quantitative Finance        数量金融学
二级分类:Economics        经济学
分类描述:q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学,包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
--

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英文摘要:
  The objective of this study is to understand how senders choose shipping services for different products, given the availability of both emerging crowd-shipping (CS) and traditional carriers in a logistics market. Using data collected from a US survey, Random Utility Maximization (RUM) and Random Regret Minimization (RRM) models have been employed to reveal factors that influence the diversity of decisions made by senders. Shipping costs, along with additional real-time services such as courier reputations, tracking info, e-notifications, and customized delivery time and location, have been found to have remarkable impacts on senders' choices. Interestingly, potential senders were willing to pay more to ship grocery items such as food, beverages, and medicines by CS services. Moreover, the real-time services have low elasticities, meaning that only a slight change in those services will lead to a change in sender-behavior. Finally, data-science techniques were used to assess the performance of the RUM and RRM models and found to have similar accuracies. The findings from this research will help logistics firms address potential market segments, prepare service configurations to fulfill senders' expectations, and develop effective business operations strategies.
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PDF链接:
https://arxiv.org/pdf/1902.08681
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关键词:maximization Minimization Quantitative Contribution Expectations 物流 RRM 市场 such data

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