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Refining spatial models of individual level consumer channel and store choice behaviours

Refining spatial models of individual level consumer channel and store choice behaviours
完善个人层面的消费者渠道和商店选择行为的空间模型
批准号:
1948587
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2017
资助国家:
英国
项目状态:
已结题
起止时间:
2017 至 --

项目摘要

项目成果

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中文摘要
翻译
背景:利兹大学空间分析和政策中心一直以其在应用零售建模和食品杂货市场选址规划方面的优势而闻名。当前使用的零售空间交互模型允许我们看到杂货市场在零售商数量、商店规模和居住在他们所在地区的人口类型方面的现状。使用该模型,零售商可以看到他们的表现如何,他们的竞争对手是谁,以及他们可以做些什么来提高收入。然而,该模型需要改进,以包括对消费者商店和渠道选择的预测,因为不同人群的情况不同,将这种个性添加到SIM需要进行大量研究,并在方法论中证明其合理性。该项目将获得客户购买和行为数据源自塞恩斯伯里的忠诚卡计划。这些数据将使该项目能够在消费者层面上捕获、理解和模拟消费者行为。这将通过使用定制的基于代理的模型中的数据并应用空间交互模型的知识和优势来实现。目标:-扩展关于消费者商店和下水道选择行为的知识。-建立一个基于代理人的模型,利用塞恩斯伯里的忠诚卡计划得出的数据进行研究,以及空间互动模型的优势。-发布一个项目,其中包括对零售世界中个人决策和行为的后果的新见解和理解。方法:为了实施这个项目,将产生一个全面的文献综述,讨论零售业在过去几十年中发生了怎样的变化,消费者可以获得哪些新的零售渠道,以及这可能对零售地点选择的影响。这将包括一个关于消费者不同购物方式的部分,以及他们的购物频率、任务和预算有何不同。它将强调,当零售商寻求扩大、改变或搬迁门店时,承认个性化消费者行为的重要性。下一节将涉及将忠诚卡计划数据转换为易于合并到模型中的格式。将设计一个基于代理的定制模型,以包括消费者的不同行为和渠道选择。这将通过借鉴已经成功和彻底发展的空间相互作用模型中使用的方法来实现。该模型将涉及个人消费者层面的选择和行为、商店类型和零售渠道,以及地理因素。这可能会有所变化,因为项目要复杂得多,但这是对拟议项目及其涉及的内容的简单总结。
英文摘要
Context: The Centre of Spatial Analysis and Policy at the University of Leeds has been known for its strength in applied retail modelling and work within location planning for the grocery market. The current retail spatial interaction model used allows us to see the grocery market as it is in terms of the number of retailers, their store sizes, and the types of populations residing in areas they are located. Using the model allows retailers to see how well they are performing, who their competitors are, and what they could do to improve revenue. However, the model requires refinements to include the prediction of consumer store and channel choices, as differs among populations and adding such individuality to a SIM requires significant research and justification within methodologies. This project will have access to customer purchasing and behaviour data derived from the Sainsbury's loyalty card scheme. This data will allow this project to capture, understand, and model consumer behaviours at the consumer level. This will be achieved through using the data in a custom-built agent based model and applying the knowledge and strength of spatial interaction models.Objectives: - To expand knowledge on consumer store and chancel choice behaviours. - To build an agent-based model that utilises the data derived from Sainsbury's loyalty card scheme for research, along with the strengths of the spatial interaction model.- To publish a project that includes new insights and understandings into the consequences of individual decision and behaviour in the retail world. Method: To carry out this project, a thorough literature review will be produced that discusses how retail has changed over the past decades, what new channels of retailing are available to consumers, and the possible impacts of this upon retail site location choices. This will include a section about the different ways consumers shop, how their shopping frequencies, missions, and budgets differ. It will highlight the importance of acknowledging individualised consumer behaviours when retailers are looking to expand, change, or relocate their stores. The next section will involve transforming the loyalty card scheme data into a format that is easy to incorporate into a model. A custom-built agent based model will be designed to include the different behaviours and channel choices of consumers. This will be achieved by drawing upon the methods used in spatial interaction models that have been successful and thoroughly developed. The model will involve individual consumer level choices and behaviours, the type of stores and channels of retail, and an element of geography. This is subject to change as the project is much more complex, however this is a simple summary of the proposed project and what it will involve.
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