Incorporating e-commerce (home deliver and 'click and collect') in grocery sector retail location modelling

英国零售杂货市场在基于零售位置的决策方法方面处于领先地位。复杂的空间互动模型（SIMs）是捕捉零售供需之间互动的强大工具，并用于预测消费者基于可达性和个体商店感知吸引力之间权衡的商店选择行为。考虑到杂货店购物和商店选择行为的传统习惯性质，他们已经能够相当准确地捕捉到消费者的行为。由于消费者越来越倾向于在网上购物，订购杂货送货上门或“点击提货”，消费者的互动变得越来越复杂。电子商务消费者对零售商（以及“点击提货”的商店）的选择是由一系列不同的因素驱动的，而这些因素在传统的杂货SIM卡中得到了体现。品牌吸引力和送货上门的可用性、可靠性或价格可能比商店规模或可及性等传统指标更重要。因此，有必要调整SIMs以捕捉这些复杂的多渠道消费者互动，并认识到电子商务食品杂货的需求和供应有其独特的消费者行为和供给侧动态。目标和方法我有三个相互关联的目标，每个目标代表一年的博士课程：了解食品杂货行业电子商务需求和供应的动态。我将根据地理位置和人口特征分析杂货行业的消费者电子商务行为（在线购物倾向、频率和典型消费、渠道使用），以建立对在零售模型中估计电子商务需求的需求的理解。我将评估当前的电子商务供应（商店网络、暗店、点击提货设施、送货上门的集水区），以在建模框架内告知多渠道供应的表示。数据来源将包括：-免费提供的二级数据集，如互联网用户分类-YouGov消费者调查数据（通过向利兹大学的CDRC申请作为安全数据集提供）-拟议的主管正在与一家主要的杂货零售商（也是CDRC的合作伙伴）进行讨论，后者可能提供额外的商店和消费者层面的电子商务交易数据。开发一个空间互动模型来捕捉食品杂货行业的多渠道消费者行为。经过校准以表示在目标1中观察到的供需动态，可能包括：-按消费者类型在线购物的倾向，生成一组细微的小区域电子商务需求估计。-渠道、品牌和店铺选择的具体驱动因素，以模拟消费者与供应方的新型互动。将我的模型应用于一系列案例研究，以证明其对零售业的潜在价值。我会选择“如果……怎么办？”的分析，以展示我的SIM在各种电子商务增长情景下基于位置的决策的价值：-评估哪些商店有“能力”挑选和包装电子商务订单-确定新的点击和收集设施的合适位置-为新的“暗店”提供服务或增加容量的位置规划-定义电子商务送货上门的“服务区域”，考虑竞争和邻近。据估计，到2020年，英国在线杂货市场的价值将达到150亿英镑，这项研究的影响超出了传统的以商店为基础的杂货零售商。该项目将提供对杂货电子商务需求特征和供应动态的新认识，以增强在零售模型框架内整合多渠道消费者行为的能力。应用案例研究将展示商业部门的利益，以及研究在基于战略位置的决策中的实际应用。

The UK retail grocery market is at the forefront of methodological advances in retail location-based decision making. Sophisticated Spatial Interaction Models (SIMs) are robust tools to capture interactions between retail supply and demand and are used to predict consumers' store-choice behaviours based on a trade-off between the accessibility and perceived attractiveness of individual stores. They have been able to capture consumer behaviours with considerable accuracy given the traditionally habitual nature of grocery shopping and store-choice behaviours. Consumer interactions are becoming more complex due to the increasing propensity for consumers to shop online, ordering groceries for home delivery or 'click and collect'. E-commerce consumers' choice of retailer (and store for 'click and collect') is driven by a different range of factors to those captured in a traditional grocery SIM. Brand attractiveness and the availability, reliability or price of home delivery may be more important than traditional indicators of store size or accessibility. There is thus a need to adapt SIMs to capture these complex multi-channel consumer interactions, recognising that e-commerce grocery demand and supply has its own unique set of consumer behaviours and supply side dynamics. Objectives and Method I have three interlinked objectives, each representing one year of the PhD programme: Understand the dynamics of grocery sector e-commerce demand and supply. I will analyse consumer e-commerce behaviours in the grocery sector (propensity to shop online, frequency and typical spend, channel usage) by location and geodemographic characteristics to build up an understanding of the demand for use in estimating e-commerce demand within a retail model. I'll assess current e-commerce supply (store networks, dark stores, click-and-collect facilities, home delivery catchment areas) to inform the representation of multi-channel supply within a modelling framework. Data sources will include: -Freely available secondary datasets such as the Internet Users Classification -YouGov consumer survey data (available as a secure dataset via application to the CDRC, at the University of Leeds) -The proposed supervisor is in discussion with a major grocery retailer (also a CDRC partner) who are likely to provide additional store and consumer level e-commerce transaction data. Develop a spatial interaction model to capture grocery sector multi-channel consumer behaviours. Calibrated to represent supply and demand dynamics observed in objective 1 and likely to include: - Propensity to shop online by consumer type, generating a nuanced set of small-area e-commerce demand estimations. - Specific drivers of channel, brand and store choice to model novel consumer interactions with the supply side. Apply my model to a range of case studies to demonstrate its potential value to the retail sector. I will undertake 'what if?' analysis to demonstrate the value of my SIM for location-based decision making under various e-commerce uptake growth scenarios: - Assessing which stores have 'capacity' to pick and pack e-commerce orders - Identify appropriate locations for new click and collect facilities - Location-planning for new 'dark stores' to service new areas or increase capacity - Defining 'service areas' for e-commerce home delivery, accounting for competition and proximity. Significance The UK online grocery market estimated to be worth £15Billion by 2020, the implications of this study go beyond traditional store-based grocery retailers. The project will provide new understanding of grocery e-commerce demand characteristics and supply dynamics to provide enhancement for incorporating mutli-channel consumer behaviour within a retail modelling framework. Applied case studies will demonstrate benefits to the commercial sector and the practical uses of the research in strategic location based decision making.