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:87
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
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
一枚小豆完成签到,获得积分10
3秒前
小乌龟完成签到 ,获得积分10
4秒前
包容雪卉完成签到 ,获得积分10
6秒前
LG完成签到,获得积分10
6秒前
zhaowenxian完成签到,获得积分10
8秒前
9秒前
Jacky77完成签到,获得积分10
11秒前
言辞完成签到,获得积分10
13秒前
cappuccino完成签到 ,获得积分10
13秒前
夏夏完成签到,获得积分10
14秒前
14秒前
15秒前
走走发布了新的文献求助10
15秒前
16秒前
研友_VZG7GZ应助夏夏采纳,获得10
17秒前
qing完成签到,获得积分10
18秒前
星辰大海应助重要思真采纳,获得10
19秒前
满意妙梦发布了新的文献求助10
20秒前
云上人完成签到 ,获得积分10
21秒前
单薄咖啡豆完成签到,获得积分10
21秒前
传奇3应助午梦千山采纳,获得10
21秒前
zhoushishan发布了新的文献求助10
22秒前
科目三应助Cmqq采纳,获得10
28秒前
wang完成签到 ,获得积分10
28秒前
wanci应助R18686226306采纳,获得10
29秒前
悄悄拔尖儿完成签到 ,获得积分10
30秒前
30秒前
Uncanny完成签到,获得积分10
31秒前
甜美帅哥完成签到,获得积分10
31秒前
31秒前
甜甜的以筠完成签到 ,获得积分10
33秒前
violet完成签到 ,获得积分10
34秒前
图图完成签到 ,获得积分10
34秒前
重要思真发布了新的文献求助10
34秒前
lifeng完成签到 ,获得积分10
36秒前
36秒前
脑洞疼应助忧郁曼云采纳,获得10
36秒前
午梦千山完成签到,获得积分10
36秒前
issie完成签到,获得积分10
40秒前
zhoushishan完成签到,获得积分10
42秒前
高分求助中
(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
Mechanics of Solids with Applications to Thin Bodies 5000
Encyclopedia of Agriculture and Food Systems Third Edition 2000
Clinical Microbiology Procedures Handbook, Multi-Volume, 5th Edition 临床微生物学程序手册,多卷,第5版 2000
人脑智能与人工智能 1000
King Tyrant 720
Principles of Plasma Discharges and Materials Processing, 3rd Edition 400
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5599548
求助须知:如何正确求助?哪些是违规求助? 4685229
关于积分的说明 14838214
捐赠科研通 4669062
什么是DOI,文献DOI怎么找? 2538076
邀请新用户注册赠送积分活动 1505449
关于科研通互助平台的介绍 1470833