An Empirical Investigation of Manufacturers’ Operations Innovations in New Product Development Enabled by E-Commerce Platforms

新产品开发 业务 产品(数学) 计算机科学 产业组织 运营管理 过程管理 商业 营销 制造工程 经济 工程类 几何学 数学
作者
Yiying Zhang,Xiao-Song Peng,Xiande Zhao,Yang Lei
出处
期刊:Production and Operations Management [Wiley]
被引量:7
标识
DOI:10.1177/10591478231224958
摘要

E-commerce platforms are playing an increasingly important role in influencing manufacturers’ supply chain and product decisions. An emerging supply chain innovation, known as the platform-based consumer-to-manufacturer (PC2M) model, has been initiated by several large e-commerce platforms based on established digital links between consumers and manufacturers. These links enable consumer inputs into manufacturers’ operations, indirectly by capturing consumer preferences from platform-accumulated big data and directly by enabling consumer interaction with manufacturers through the e-commerce platform. Although manufacturers are increasingly integrating PC2M into new product development (NPD), there is little research on operations innovations in connection with the PC2M model and its impact on manufacturers’ new product success. To fill this research gap, we investigate the PC2M model of JD.com, a leading e-commerce platform in China that launched the PC2M model in 2018. We first identify two uses of PC2M by manufacturers to facilitate product development—platform-enabled big data analytics (PBA) and platform-enabled simulated product trials (PST)—and explore how PC2M enables operations innovations in NPD. Next, drawing on the knowledge-based view, we develop research hypotheses and empirically examine whether PC2M adoption improves new product performance using a large-scale, transactional dataset from JD.com. Through a series of carefully executed analyses, our study consistently finds that use of either PBA or PST in manufacturers’ NPD processes improves new product performance. We also explore how these effects vary across product types and markets with varying new product introduction rates. The findings offer important managerial insights for improving new product success in today's data-rich environment.
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
1秒前
称心的语梦完成签到,获得积分10
1秒前
老实的棉花糖完成签到,获得积分10
2秒前
2秒前
昆仑发布了新的文献求助10
2秒前
3秒前
xixi0816发布了新的文献求助10
4秒前
4秒前
With发布了新的文献求助10
5秒前
5秒前
5秒前
精明一寡发布了新的文献求助10
5秒前
cocoa345发布了新的文献求助10
5秒前
书山有路勤为径完成签到 ,获得积分10
6秒前
7秒前
songnvshi完成签到 ,获得积分10
7秒前
顺心不愁发布了新的文献求助10
7秒前
苹果幻儿发布了新的文献求助10
8秒前
xieqian发布了新的文献求助10
8秒前
冷傲方盒完成签到,获得积分10
9秒前
科研通AI6.2应助Leonard采纳,获得10
9秒前
sun完成签到,获得积分10
9秒前
沐小悠发布了新的文献求助10
9秒前
在下某林发布了新的文献求助10
9秒前
命苦科研人完成签到 ,获得积分10
9秒前
10秒前
11秒前
12秒前
科目三应助爱听歌的谷秋采纳,获得10
12秒前
小洪包发布了新的文献求助10
12秒前
13秒前
斯文败类应助piglet采纳,获得10
13秒前
xixi0816完成签到,获得积分10
13秒前
我是老大应助唠叨的轩轩采纳,获得10
14秒前
老刘爱吃饭完成签到,获得积分10
15秒前
SciGPT应助Jason采纳,获得10
16秒前
苹果幻儿完成签到,获得积分20
17秒前
Copyright应助魏欣娜采纳,获得10
17秒前
旧人旧街发布了新的文献求助10
18秒前
18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
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场现状调查及投资机会研判报告 1000
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场规模及竞争格局分析报告 1000
48V Low-voltage Power Distribution Network (PDN) Architecture Industry Report, 2024 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
Introducing the Learning Sciences 600
Resiliency Scale for Adolescents--Chinese Version 600
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 7322405
求助须知:如何正确求助?哪些是违规求助? 8937794
关于积分的说明 18949344
捐赠科研通 6980185
什么是DOI,文献DOI怎么找? 3215009
关于科研通互助平台的介绍 2382510
邀请新用户注册赠送积分活动 2194225