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
luodaxia发布了新的文献求助10
刚刚
萧拾壹发布了新的文献求助10
刚刚
JamesPei应助心灵美乐瑶采纳,获得10
1秒前
小慧完成签到,获得积分10
1秒前
不麻怎么吃完成签到,获得积分10
1秒前
所所应助余杭村王小虎采纳,获得10
1秒前
无奈冥完成签到,获得积分10
2秒前
充电宝应助沉默的山河采纳,获得10
2秒前
2秒前
隐形曼青应助奈落采纳,获得10
3秒前
CipherSage应助Nobody采纳,获得10
3秒前
wm发布了新的文献求助10
3秒前
4秒前
4秒前
111发布了新的文献求助10
5秒前
5秒前
wuy完成签到,获得积分10
6秒前
6秒前
闪闪凌文完成签到 ,获得积分10
6秒前
脑洞疼应助端庄天玉采纳,获得10
6秒前
Lucas应助chenhouhan采纳,获得10
7秒前
像只猫完成签到,获得积分10
7秒前
科研通AI6.1应助小超人采纳,获得10
7秒前
上好佳发布了新的文献求助10
8秒前
慕青应助完美的问旋采纳,获得10
8秒前
仇悦完成签到,获得积分10
8秒前
梦隐雾完成签到,获得积分10
8秒前
luodaxia完成签到,获得积分10
8秒前
9秒前
125676完成签到,获得积分10
9秒前
9秒前
诸岩完成签到,获得积分10
9秒前
ding应助miao采纳,获得10
10秒前
10秒前
大模型应助迅速的岩采纳,获得10
10秒前
Akim应助标致幼菱采纳,获得10
10秒前
11秒前
Alan发布了新的文献求助20
11秒前
11秒前
11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
Introduction to Helicopter and Tiltrotor Flight Simulation, Second Edition 2500
卤化钙钛矿人工突触的研究 2000
Malcolm Fraser : a biography 700
Signals, Systems, and Signal Processing 610
Software that combines deep learning,3D reconstruction and CFD to analyze the state of carotid arteries from ultrasound imaging 600
Bounds for Statistical Estimation in Semiparametric Models 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 6499967
求助须知:如何正确求助?哪些是违规求助? 8295350
关于积分的说明 17702644
捐赠科研通 5596542
什么是DOI,文献DOI怎么找? 2918192
邀请新用户注册赠送积分活动 1895260
关于科研通互助平台的介绍 1756131