When Does the Pre-entry Experience of New Entrants Improve Their Performance? A Meta-Analytical Investigation of Critical Moderators

背景(考古学) 经验证据 营销 产业组织 业务 实证研究 进入壁垒 荟萃分析 资产(计算机安全) 经济 计算机科学 市场结构 生物 认识论 内科学 哲学 医学 古生物学 计算机安全
作者
Zhi Cao,Hart E. Posen
出处
期刊:Organization Science [Institute for Operations Research and the Management Sciences]
卷期号:34 (2): 613-636 被引量:13
标识
DOI:10.1287/orsc.2022.1589
摘要

Although pre-entry experience is widely regarded as a critical asset that positively influences new entrant performance, empirical support is mixed. To address this inconsistency, we conduct a meta-analysis of the empirical findings in 272 papers. We draw theoretically on the organizational learning literature to argue that the pre-entry experience–new entrant performance relationship is contingent on the characteristics of pre-entry experience, the environmental context of the new entrant, and the interaction between the two. In particular, we examine the effects of two levels of pre-entry experience (firm and founder), four types of founder-level pre-entry experience (entrepreneurial, managerial, industry, and functional experience), and two types of environments (industry and institutional). The meta-analysis results show a significant and positive correlation between founder-level pre-entry experience and economic performance of 0.07. Likewise, the failure rates of spinouts and diversifying entrants are 11% lower than that of start-ups. The moderating analysis results show that the correlation of founder-level pre-entry experience and economic performance is lower in knowledge- or technology-intensive (KTI) industries and higher in low-KTI manufacturing and service industries. The correlation is also higher in institutional environments with high power distance and individualism. These findings provide compelling new evidence for the importance of pre-entry experience and advance our understanding of the boundary conditions on the pre-entry experience–new entrant performance relationship. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2022.1589 .
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
打打应助spinon采纳,获得10
1秒前
Yy完成签到 ,获得积分10
1秒前
2秒前
3秒前
斯文败类应助周周采纳,获得10
4秒前
赖林完成签到,获得积分10
4秒前
丁久洋给丁久洋的求助进行了留言
4秒前
5秒前
福团团完成签到,获得积分10
5秒前
6秒前
yuan完成签到,获得积分10
7秒前
星空完成签到,获得积分10
8秒前
忽昨日完成签到,获得积分10
8秒前
lyy发布了新的文献求助10
9秒前
Mumu发布了新的文献求助10
9秒前
10秒前
11秒前
12秒前
hudu完成签到,获得积分10
13秒前
15秒前
16秒前
li发布了新的文献求助10
16秒前
16秒前
hzy发布了新的文献求助10
16秒前
Cecilia完成签到,获得积分10
16秒前
大模型应助Planet_Rabbit采纳,获得30
16秒前
快乐战神没烦恼完成签到,获得积分10
17秒前
21秒前
Dita发布了新的文献求助10
22秒前
Imp完成签到,获得积分10
22秒前
spinon发布了新的文献求助10
23秒前
超越俗尘完成签到,获得积分10
23秒前
笨笨志泽完成签到,获得积分10
25秒前
Chloe完成签到,获得积分10
26秒前
Orange应助唐美鸭采纳,获得10
28秒前
30秒前
素人完成签到,获得积分10
30秒前
echo完成签到,获得积分10
31秒前
希望天下0贩的0应助kun采纳,获得10
31秒前
一个one子完成签到 ,获得积分10
35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
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Various Faces of Animal Metaphor in English and Polish 800
Signals, Systems, and Signal Processing 610
Photodetectors: From Ultraviolet to Infrared 500
On the Dragon Seas, a sailor's adventures in the far east 500
Yangtze Reminiscences. Some Notes And Recollections Of Service With The China Navigation Company Ltd., 1925-1939 500
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 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6354092
求助须知:如何正确求助?哪些是违规求助? 8169101
关于积分的说明 17196078
捐赠科研通 5410215
什么是DOI,文献DOI怎么找? 2863906
邀请新用户注册赠送积分活动 1841349
关于科研通互助平台的介绍 1689961