Omni-Channel Retailing and Firm Performance from a Customer Lifetime Value Perspective

In the digital era,retailers are keen to find out whether omni-channel retailing helps improve long-term firm performance.In this paper,we employ machine learning techniques on a large consumption data set in order to measure customer lifetime value(CLV)as the basis for determining long-term firm performance,and we provide an empirical analysis of the relationship between omni-channel retailing and CLV.The results suggest that omni-channel retailing may effectively enhance CLV.Further analysis reveals that this process is influenced by heterogeneous consumer requirements and that significant differences exist in the extent to which the omni-channel transition may influence CLV depending on consumer preferences for diversity of commodities,sensitivity to the cost of contract performance,and sensitivity to warehousing costs.Hence,retailers should provide consumers with a complete portfolio of goods and services based on target consumers’heterogeneous requirements in order to increase omni-channel efficiency.

The Interrelationship between Culture and Capital Structure:Evidence from International Retailers

The present study investigates the influence of cultural factors in 2022 on the capital structure of global retailers.There are sixteen retailers from eight countries in the sample.In recent times,numerous academicians have taken an interest in examining the capital structure and business model of retailers,owing to their swift and consistent growth.However,the fact that the majority of research originates from the retailers’host country gives rise to debate regarding the applicability of the capital structure of said retailers to countries with distinct cultural environments.Consequently,academics have begun to investigate whether the capital structure of multinational retailers is impacted by the diversity of national cultures.

More and More Retail Brands Integrate ESG into Development

Recently, Savills and the U.S. Green Building Council released Sustainable Retail-Staying on Track(hereinafter the report), which pointed out that the ranking of the 20-city retailer index in 2022 changed the most in the past five years, but that Shanghai, Beijing, Shenzhen and Chengdu are still among the top four retailers in 2022. The sustainable retail index of coastal cities including Ningbo, Qingdao and Xiamen has greatly improved.

Assessment of the Retail Food Environment Using Integrated GIS and Modified Measures in Wuhan, China

The retail food environment (RFE) has a significant impact on people’s dietary behavior and diet-related outcomes. Although RFE research has received a lot of attention, there are very few studies that shed light on the foodscape and assessment methodologies in the China context. Based on open data obtained from Dianping.com and AutoNavi map, we classified all food outlets into six types. Geographic Information Systems (GIS) techniques were employed to create two network buffer areas (1-km and 3-km) and calculate the absolute measures and relative measures (i.e., mRFEI and Rmix). We modified the calculation of relative measures by adding items and assigning weights. The mean mRFEI using the 1-km and 3-km buffer sizes across the communities were 10.45 and 20.12, respectively, while the mean mRmix of the two buffer sizes were 20.97 and 58.04, indicating that residents in Wuhan have better access to fresh and nutritious food within 3-km network buffers. Residents in urban areas are more likely to be exposed to an unhealthy food environment than those in rural areas. Residents in Xinzhou and Qiaokou districts are more likely to be subjected to unfavorable neighborhood RFE. The open data-driven methods for assessing RFE in Wuhan, China may guide community-level food policy interventions and promote active living by shifting built environments to increase residents’ access to healthy food.

Optimization of Electricity Purchase and Sales Strategies of Electricity Retailers under the Condition of Limited Clean Energy Consumption

In the process of my country’s energy transition,the clean energy of hydropower,wind power and photovoltaic power generation has ushered in great development,but due to the randomness and volatility of its output,it has caused a certain waste of clean energy power generation resources.Regarding the purchase and sale of electricity by electricity retailers under the condition of limited clean energy consumption,this paper establishes a quantitative model of clean energy restricted electricity fromthe perspective of power system supply and demand balance.Then it analyzes the source-charge dual uncertain factors in the electricity retailer purchasing and selling scenarios in the mid-to long-term electricity market and the day-ahead market.Through the multi-scenario analysis method,the uncertain clean energy consumption and the user’s power demand are combined to form the electricity retailer’s electricity purchase and sales scene,and the typical scene is obtained by using the hierarchical clustering algorithm.This paper establishes a electricity retailer’s risk decisionmodel for purchasing and selling electricity in themid-and long-term market and reduce-abandonment market,and takes the maximum profit expectation of the electricity retailer frompurchasing and selling electricity as the objective function.At the same time,in themediumand longterm electricity market and the day-ahead market,the electricity retailer’s purchase cost,electricity sales income,deviation assessment cost and electricity purchase and sale risk are considered.The molecular results show that electricity retailers can obtain considerable profits in the reduce-abandonment market by optimizing their own electricity purchase and sales strategies,on the premise of balancing profits and risks.

Customer Segment Prediction on Retail Transactional Data Using K-Means and Markov Model

Retailing is a dynamic business domain where commodities and goods are sold in small quantities directly to the customers.It deals with the end user customers of a supply-chain network and therefore has to accommodate the needs and desires of a large group of customers over varied utilities.The volume and volatility of the business makes it one of the prospectivefields for analytical study and data modeling.This is also why customer segmentation drives a key role in multiple retail business decisions such as marketing budgeting,customer targeting,customized offers,value proposition etc.The segmentation could be on various aspects such as demographics,historic behavior or preferences based on the use cases.In this paper,historic retail transactional data is used to segment the custo-mers using K-Means clustering and the results are utilized to arrive at a transition matrix which is used to predict the cluster movements over the time period using Markov Model algorithm.This helps in calculating the futuristic value a segment or a customer brings to the business.Strategic marketing designs and budgeting can be implemented using these results.The study is specifically useful for large scale marketing in domains such as e-commerce,insurance or retailers to segment,profile and measure the customer lifecycle value over a short period of time.

竞争环境下网络零售商线下渠道策略研究

网络零售商是否选择开设线下渠道是其面临的重要决策问题.本文考虑竞争环境下网络零售商是否开设线下渠道问题,重点关注其是否开设线下展厅及是否提供产品销售策略.为此,首先分别考虑两个零售商不提供展厅策略、同时提供展厅策略、同时提供展厅策略并销售产品三种情形,并进一步考虑仅有一个零售商开设展厅策略的情形,建立相应的决策模型.研究发现:(1)零售商是否提供展厅策略与市场中具有较高旅行成本的消费者比例、市场竞争程度及展厅建设成本具有显著的关联性;(2)当零售商提供展厅策略时,其是否进行产品销售与线下渠道的消费者比例具有显著的关联性;(3)产品退货率高低与消费者交叉展厅行为对零售商是否提供展厅策略具有一定的影响.本文的研究对电商企业及网络零售商的渠道选择决策提供了科学的决策依据.

县域农产品网络零售发展的影响因素与组态路径——基于34个县域案例的清晰集定性比较分析

基于TOE框架,依据我国34个县域案例,运用清晰集定性比较分析方法,探讨技术、组织、环境条件对县域农产品网络零售发展影响因素的联动效应及其路径选择,探索性地识别出三类推动县域农产品网络零售快速发展的适配性方案。研究发现,单一条件不是县域农产品网络零售快速发展的必要条件,某个或某些方面不具优势的县域,可以通过组态路径实现快速发展;促使农产品网络零售快速发展具有多样化的组态路径,且不同县域农产品网络零售快速发展的路径存在差异,不同条件的变量组合可以实现殊途同归,这些组态可分为组织驱动型、环境驱动型和组织环境驱动型三种;行业发展水平和财政支农力度是农产品网络零售快速发展普遍需求的两个核心条件,表明农产品网络零售发展需要产业结构转型和财政资金的支持;对数字技术水平较高的县域,在维持一定的政策制度保障和财政支农力度下,行业发展水平可以和特色品牌塑造相互替代。县域需要综合考虑多种条件的联动作用,提升行业发展水平、加大财政支持力度、夯实政策制度保障、强化数字技术支撑和提升特色品牌价值,充分发挥技术、组织和环境条件之间的协同效应,因地制宜采取符合自身实际的组合路径,促进农产品网络零售高质量发展,助力农民增收创收和乡村全面振兴。

得零售者可以得天下——基于银行利润效率视角

零售业务作为商业银行的基础业务和战略性业务,已经成为中国银行业整体收入增长的主要动力。本文以我国48家商业银行2011—2021年的数据为研究对象,以产出定位的非单调异质性随机前沿方法为基础,测度了商业银行的利润效率水平,并利用2SLS探究零售业务对银行利润效率的整体影响。研究发现,银行零售业务的发展能够有效地提高银行的利润效率,尤其是信用卡业务对利润效率的正向影响最大,个人住房抵押贷款对利润效率的影响次之,消费贷和经营贷的影响最小;第二,国有银行、股份制银行的零售业务对利润效率的促进程度远高于城商行和农商行;第三,中国银行业利润效率整体呈上升趋势,其中,股份制银行的利润效率水平位居榜首,城商行利润效率自2011年以来一路上升,2021年增长到0.5872,而农商行的利润效率水平最低。

考虑配送交通风险的新零售平台、骑手及消费者三方演化博弈分析

新零售行业中配送骑手的交通事故比率不断攀升引起了社会的广泛关注。骑手出于对配送超时和消费者投诉的担心,在配送途中选择超速违章,从而增加交通风险。为避免消费者对配送超时进行投诉,越来越多的平台企业主动建立超时补偿机制,即对配送超时为消费者提供补偿。该补偿机制能否有效减少消费者投诉,进而影响骑手的配送行为,降低其配送中的交通风险,是值得研究的重要问题。构建由新零售平台、骑手及消费者组成的三方演化博弈模型,其中,平台决定是否建立针对消费者的超时补偿机制,骑手在不同风险程度的配送行为之间进行选择,而消费者则决定在超时情况下是否进行投诉。研究发现:平台对于骑手超时的直接惩罚额度是影响骑手的策略中最关键的影响因素。当直接惩罚额度较大时,平台、消费者的任何策略选择都无法改变骑手普遍向高风险配送策略演化的“骑手困境”情况;当直接惩罚额度适中,建立超时补偿机制给平台企业带来的直接效用较大,且平台与消费者普遍对骑手更具有同理心时,三方演化策略均衡可以达到理想状态:平台建立主动补偿机制、骑手低风险配送、消费者对于订单超时选择不投诉。

数字经济赋能零售企业国际化:机制、制约与对策

中国零售企业依托数字技术加快国际化,融入或主导构建全球供应链的探索有助于服务构建新发展格局。从价值共创的理论视角看,数字经济赋能零售企业国际化的机制包括与消费者、供应商和同业企业的价值共创。当前数字经济赋能中国零售企业国际化的效应已初步显现,但仍处于起步阶段,存在采购国际化中数字经济赋能主体范围与环节有限、店铺运营国际化尚未形成规模效应、专业技能国际转移面临全球数字贸易规则博弈带来的不确定性等问题与制约。文章建议引导零售企业协同多方主体推进采购国际化,政策赋能推动零售企业店铺运营国际化,提升数字话语权为零售专业技能国际转移护航,并在数字“一带一路”框架下推进零售企业国际化。

门诊共济保障方式改革、零售药店发展与处方流转

职工医保门诊共济保障改革是完善基本医保制度的重大举措。本次改革将符合条件的定点零售药店纳入门诊统筹报销,为零售药店的高质量发展带来重大机遇。门诊共济保障改革以及零售药店实现高质量发展的关键环节是医院处方的流转。本文认为,处方流转的主要障碍一是处方管理及药品使用安全管理上的部门分割以及由此带来的风险责任冲突及利益冲突,二是零售药店本身的经营与管理模式还难以适应处方的风险管理要求。实现处方的畅通流转一是要坚持“三医”协同治理,建立处方管理及药品使用安全管理全链条监管机制,打破部门分割,充分尊重参与各方的管理要求及利益诉求;二是零售药店要转变运营模式,提升药事服务和商业服务能力,适应门诊共济保障改革后处方流转的要求。

数字经济背景下江苏新零售模式创新研究

随着数字经济的快速发展,数字化的高质量转型已成为各个领域的重要挑战。在数字经济背景下,传统零售行业诞生出新模式——“新零售”,在数字技术的发展与带动下,零售行业各个环节都面临着重塑的局面。江苏作为经济大省,其新零售行业也在快速发展,并不断寻找新的发展机遇以应对各种新型商业模式的挑战。本文通过对江苏新零售发展现状及所面临问题的全面分析,从数字经济的角度系统探讨了新零售模式创新的理论框架和实施路径。研究表明,数字经济的引入有助于优化决策机制,推动新零售企业以数据驱动决策,进而提升新零售模式的创新能力和市场竞争力。本文提出了建立以数据为基础的决策机制、引入先进的算法和技术、加强线上线下融合、提升消费者体验等策略建议,旨在为江苏省新零售行业的创新发展提供具有参考价值的策略方案。

监管型小股东对股价同步性的影响研究

基于2016年2月中证中小投资者服务中心(简称投服中心)持股行权试点的研究场景,采用双重差分法考察投服中心对公司股价同步性的影响。研究发现:作为监管型小股东,投服中心持股行权降低了公司的股价同步性。进一步地,投服中心对股价同步性的影响在分析师关注度较低、媒体报道较少时更显著。机制检验显示,投服中心成立后上市公司的信息披露质量提高,管理层业绩预告质量改善,产生了信息效应;投服中心行权引起媒体和监管部门的关注,可减少大股东的利益侵占行为,提高中小股东参与股东大会的积极性,发挥出治理效应。

零售商主导供应链中物流服务共享的影响研究

随着零售业的快速发展,零售商的话语权不断提升,有越来越多的零售商开始成为供应链的主导者。在零售业中,零售商在批发零售的同时又为第三方卖家提供零售平台已经成为了一种主流的商业模式。此外,一些零售商开始向第三方卖家共享其自建物流服务。本文研究了在零售商主导的供应链中零售商的物流服务共享(简称LSS)对于供应商、第三方卖家、整个供应链以及消费者的影响。本文构建了一个包含供应商、零售商和第三方卖家的博弈模型,研究结果表明:(1)LSS总是对第三方卖家的价格、需求和利润产生积极影响。(2)跨渠道服务敏感性较小时,LSS能够实现供应商、第三方卖家和零售商三方共赢。(3)当零售商的物流服务水平并不比第三方物流服务水平高太多时,LSS可以提升供应链总利润;跨渠道服务敏感性中等时,LSS可以提升消费者效用。

基于总注视时长的自动售货机智能推荐系统实验研究

目的 如何缓解消费者面对系列文创产品的决策困难问题,辅助消费者决策并提升购物体验是无人零售领域亟待解决的问题,眼动追踪技术为无人零售的人机交互体验提供了新机遇。方法 针对文创售货机,利用眼动追踪技术提出了一种基于总注视时长的自动售货机单因素智能推荐方法,搭建了文创售货机货柜模拟场景完成实验验证。经过眼动数据分析结合主观访谈,探讨分析了该方法对消费者购买意图的预测情况,以及在不同推荐策略下的推荐效果。结果 利用此推荐方法,当推荐3个商品时,命中至少1个消费者意愿购买商品的概率为97.92%,且命中最爱商品概率为78.13%。结论 该智能推荐方法能够有效预测消费者的购买意图、缩小决策范围辅助决策,并为实现自动售货机的智能化导购提供研究基础。

皮革产品零售企业的品牌战略研究

随着我国皮革产业的高速发展,涌现出一批具有市场竞争意识和品牌意识的零售企业。在品牌影响力不断提升情形下,它们为产业发展起到促进作用。新时期,皮革产品零售面临形势更加复杂。对于零售企业而言,必须要适应时代发展要求,强化对品牌建设的重视程度,构建具有促进和引导作用的品牌战略体系,为销售水平提升起到积极促进作用,为企业实现发展目标奠定坚实基础。

新零售背景下卡车与无人机协同的电商物流末端配送优化

消费需求与用户体验是电商新业态的关注重点,电商物流作为其中重要的一环,在末端配送中仍以低成本为导向,消费者“门到门”配送需求没有得到完全满足。为更好地满足用户的上门配送需求、提升物流服务水平,在考虑无人机载重及飞行范围的条件下,提出一种卡车与无人机协同的配送路径规划问题。以卡车与无人机综合配送成本最小为目标建立混合整数规划模型,并提出一种改进混合蚁群算法对问题进行求解,实现卡车与无人机路径的联合优化。最后,通过算例实验验证了所建模型的合理性和设计算法的有效性,为提升电商物流末端配送服务水平提供决策参考和依据。

数字经济背景下“新零售”驱动产品全渠道供应链整合优化

随着数字经济的高速发展,“新零售”模式应运而生,成为零售业一大变革。“新零售”整合线上线下多渠道资源,推动了商品供应链管理的革命。通过探讨在数字经济背景下,如何通过“新零售”模式驱动产品全渠道供应链整合优化,进而提高供应链管理的效能和响应速度。研究发现:利用大数据预测分析及其算法在精准需求预测上具有显著效果,能够有效降低库存成本,提高存货周转率;而云计算在供应链节点的信息集成处理方面显示出较强的数据处理能力和资源优化配置功能。研究结论指出:全面推进供应链的数字化变革是实现供应链体系在“新零售”发展下整合与优化的关键。

区块链食品可追溯系统对消费者惠顾意愿的影响研究

区块链能有效解决食品供应链中因信息不对称导致的食品安全问题,但是其相关技术在零售商端口如何应用且发挥作用的研究仍非常有限。因此,立足于零售商视角,基于信任理论,通过三个消费者实验,探究了区块链食品可追溯系统对消费者惠顾意愿的影响。结果表明:消费者更加倾向于惠顾采用区块链食品可追溯系统的零售商店(实验一);零售商信任(能力、善意、正直)在其中发挥中介作用(实验二);该中介作用受到广告诉求的调节,相比利己诉求,利他诉求更能通过区块链系统提升消费者的信任与惠顾意愿(实验三)。因此,食品零售商应积极采用区块链食品可追溯系统并注意配合使用相应的广告策略,政府可通过大力推动区块链食品可追溯系统在零售中的应用来更好地治理食品安全问题。