已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

Logistics Performance, Ratings, and Its Impact on Customer Purchasing Behavior and Sales in E-Commerce Platforms

采购 业务 交付性能 客户保留 营销 服务(商务) 电子商务 顾客满意度 服务质量 产品(数学) 计算机科学 过程管理 几何学 数学 万维网
作者
Vinayak Deshpande,Pradeep K. Pendem
出处
期刊:Manufacturing & Service Operations Management [Institute for Operations Research and the Management Sciences]
卷期号:25 (3): 827-845 被引量:102
标识
DOI:10.1287/msom.2021.1045
摘要

Problem definition: We examine the impact of logistics performance metrics such as delivery time and customer’s requested delivery speed on logistics service ratings and third-party sellers’ sales on an e-commerce platform. Academic/practical relevance: Although e-commerce retailers like Amazon have recently invested heavily in their logistics networks to provide faster delivery to customers, there is scant academic literature that tests and quantifies the premise that convenient and fast delivery will drive sales. In this paper, we provide empirical evidence on whether this relationship holds in practice by analyzing a mechanism that connects delivery performance to sales through logistics ratings. Prior academic work on online ratings in e-commerce platforms has mostly analyzed customers’ response to product functional performance and biases that exist within. Our study contributes to this stream of literature by examining customer experience from a service quality perspective by analyzing logistics service performance, logistics ratings, and its impact on customer purchase probability and sales. Methodology: Using an extensive data set of more than 15 million customer orders on the Tmall platform and Cainiao network (logistics arm of Alibaba), we use the Heckman ordered regression model to explain the variation in customers’ rating of logistics performance and the likelihood of customers posting a logistics rating. Next, we develop a generic customer choice model that links the customer’s likelihood of making a purchase to the logistics ratings provided by prior customers. We implement a two-step estimation of the choice model to quantify the impact of logistics ratings on customer purchase probability and third-party seller sales. Results: We surprisingly find that even customers with no promise on delivery speed are likely to post lower logistics ratings for delivery times longer than two days. Although these customers are not promised an explicit delivery deadline, they seem to have a mental threshold of two days and expect deliveries to be made within that time. Similarly, we find that priority customers (those with two-day and one-day promise speed) provide lower logistics ratings for delivery times longer than their anticipated delivery date. We estimate that reducing the delivery time of all three-day delivered orders on this platform (which makeup [Formula: see text] 35% of the total orders) to two days would improve the average daily third-party seller sales by 13.3% on this platform. The impact of delivery time performance on sales is more significant for sellers with a higher percentage of three-day delivered orders and a higher spend per order. Managerial implications: Our study emphasizes that delivery performance and logistics ratings, which measure service quality, are essential drivers of the customer purchase decision on e-commerce platforms. Furthermore, by quantifying the impact of delivery time performance on sales, our study also provides a framework for online retailers to assess if the increase in sales because of improved logistics performance can offset the increase in additional infrastructure costs required for faster deliveries. Our study’s insights are relevant to third-party sellers and e-commerce platform managers who aim to improve long-term online customer traffic and sales. History: This paper has been accepted as part of the 2018 MSOM Data Driven Research Challenge. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2021.1045 .
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
隐形曼青应助yy采纳,获得10
刚刚
彭于晏应助Hua采纳,获得10
刚刚
小马甲应助zlf采纳,获得10
刚刚
ding应助xiao苏采纳,获得10
刚刚
丘比特应助Jessica08采纳,获得10
刚刚
彭于晏应助lxy采纳,获得10
刚刚
传奇3应助向阳采纳,获得10
1秒前
深情安青应助海棠采纳,获得30
1秒前
田様应助科研通管家采纳,获得10
1秒前
情怀应助科研通管家采纳,获得10
1秒前
乐乐应助科研通管家采纳,获得10
1秒前
酷波er应助科研通管家采纳,获得10
1秒前
Lucas应助科研通管家采纳,获得10
1秒前
传奇3应助科研通管家采纳,获得10
1秒前
思源应助科研通管家采纳,获得30
2秒前
田様应助科研通管家采纳,获得10
2秒前
初景应助科研通管家采纳,获得30
2秒前
Hello应助科研通管家采纳,获得10
2秒前
大个应助科研通管家采纳,获得10
2秒前
乐乐应助科研通管家采纳,获得10
2秒前
深情安青应助科研通管家采纳,获得10
2秒前
东方元语应助科研通管家采纳,获得20
2秒前
wanci应助科研通管家采纳,获得10
2秒前
所所应助科研通管家采纳,获得10
2秒前
英姑应助尘中客采纳,获得10
3秒前
Orange应助科研通管家采纳,获得10
3秒前
3秒前
无花果应助科研通管家采纳,获得10
3秒前
英俊的铭应助科研通管家采纳,获得10
3秒前
酷波er应助科研通管家采纳,获得10
3秒前
bkagyin应助科研通管家采纳,获得10
3秒前
情怀应助科研通管家采纳,获得10
3秒前
乐乐应助科研通管家采纳,获得10
3秒前
传奇3应助科研通管家采纳,获得10
3秒前
东方元语应助科研通管家采纳,获得20
3秒前
Lucas应助科研通管家采纳,获得10
3秒前
所所应助科研通管家采纳,获得10
3秒前
思源应助科研通管家采纳,获得30
4秒前
田様应助科研通管家采纳,获得10
4秒前
ccj发布了新的文献求助10
4秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Gründe der Seele:Die Wiener Psychatrie im 20.Jahrhundert 1000
Development of a Bridge Weigh-In-Motion System: A technology to convert the bridge response to the passage of traffic into data on vehicle configurations, speeds, times of travel and weights 1000
Organic Reactions, Volume 116 1000
Current concepts in cutaneous toxicity : proceedings of the Fourth Conference on Cutaneous Toxicity, Washington, D.C., May 9-11, 1979 1000
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7273986
求助须知:如何正确求助?哪些是违规求助? 8895040
关于积分的说明 18804387
捐赠科研通 6947763
什么是DOI,文献DOI怎么找? 3205550
关于科研通互助平台的介绍 2377131
邀请新用户注册赠送积分活动 2180456