《经验与企业:职业、组织与创业

Weiyi Ng
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引用次数: 1

摘要

本文通过对构成美国高科技创业生态样本的200多万份简历的实证分析,考察了创业的前因。第一章描述了围绕创业进入研究的潜在问题(第1章)。然后,我通过创业的社会学职业框架的发展,分两部分解决了这些问题。第一章建立了框架,并区分了两种类型的创业活动:高潜力企业和普通自雇佣(第2章)。我表明,应用于数十万企业家身份声明的机器学习模型可以成功地对技术部门的这些类型进行分类、表征和区分。这两种类型的企业家表现出截然相反的人力资本和基于职业的背景。在这样做的过程中,我展示了对创业事件的必要的去合并;职业生涯框架为创业结果变量的定义、观察和测量提供了至关重要的精确性。第二部分举例说明了该框架在识别和研究特定社会学机制方面的有效性。通过引入的仪器和代表美国排名前23位的科学、技术、工程和数学(STEM)学院毕业生的前瞻性数据样本,我通过检查经历流动性事件的公司校友的不同形式的创业活动,研究了地位提升对创业进入和成功的影响:首次公开募股(ipo)和大规模收购(第3章)。我发现,在间接经历这些流动性事件后,校友进入高潜力创业的可能性平均增加23%,进入合同自营职业的可能性平均减少17%。然而,这种形式的地位获得并没有给新生企业带来显著的资金优势。最后,我讨论了未来的方向:这篇论文只是一个介绍,并倡导一个更大的研究项目,旨在通过社会学职业理论澄清和推进创业研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On Experience and Enterprise: Careers, Organizations and Entrepreneurship
This dissertation examines the antecedents of entrepreneurship through the empirical analysis of over 2 million resumes that constitutes a sample of the high technology start-up ecology in the United States. The first chapter characterizes the latent issues surrounding the study of entrepreneurial entry (Chapter 1). I then resolve these issues through the development of a sociological career framework of entrepreneurship in two parts. The first establishes the framework and distinguishes two types of entrepreneurial activity: high potential ventures and common self-employment (Chapter 2). I show that machine learning models applied to the identity claims of hundreds of thousands of entrepreneurs can successfully classify, characterize and distinguish these types in the tech sector. The two entrepreneur types exhibit diametrically opposing human capital and career based antecedents. In doing so, I demonstrate a necessary de-conflation of entrepreneurial events; the career framework provides a crucial precision in the definition, observation and measurement of the entrepreneurial outcome variable. The second part exemplifies an application of the framework to demonstrate an efficacy in the identification and study of specific sociological mechanisms. Through the introduced apparatus and a prospective sample of the data that represents the graduates of the top 23 science, technology, engineering and mathematics (STEM) colleges in the United States, I study the effect of status gain on entrepreneurial entry and success by examining different forms of entrepreneurial activity of the alumni of companies that experience liquidity events: initial public offerings (IPOs) and large scale acquisitions (Chapter 3). I find that upon vicariously experiencing these liquidity events, the alumni are on average 23% more likely to enter into high potential entrepreneurship and 17% less likely to enter into contract self-employment. However, such forms of status gain confer no significant funding advantages to the nascent venture. I conclude by discussing future directions: this dissertation serves as but an introduction to and an advocate for a larger program of research that seeks to clarify and advance the study of entrepreneurship through sociological career theory.
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