Management and Economic Performance

管理和经济绩效

• 批准号: 1823616
• 负责人: Melissa Dell
• 金额: $ 33.64万
• 依托单位: National Bureau of Economic Research Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1823616&HistoricalAwards=false
• 关键词: Management; Economic; Performance

Productivity, innovative capacity, and the ability to transition into new product spaces vary significantly across firms. These differences are central to understanding economic development and structural change, and this research focuses on one potentially important determinant: managerial capital. The context is post-war Japan, a setting that offers both a large-scale natural experiment and extremely rich data. During the occupation of Japan, Allied Forces implemented an "economic purge" of senior managers in large Japanese firms. Managers who had been employed at any time between 1937 and 1945 at firms with a net worth of over one hundred million yen were subjected to mandatory removal from their posts and barred from managerial positions in other large firms. They typically moved to firms in newer industries, which were not dominated by large conglomerates. The purge may have lowered economic performance by depriving Japan's large firms of scarce talent, or alternatively may have cleared the way for younger, innovative leaders to gain a foothold. It could have also promoted innovation by channeling talent into newer, rising industries, which tended to be exempt from the purge. However, if managerial capital is primarily embedded in organizational norms rather than in individuals, the purge may have had limited effects. This research estimates the impacts of the purge by comparing firms whose managers were purged to firms who barely avoided the purge by being just below the one hundred-million-yen cutoff. It also examines the performance of the firms to which purged managers moved. Finally, for those managers at branches that operated in colonial Taiwan, it examines whether ongoing connections with former Taiwanese employees helped these employees to subsequently transition into industries related to those of their former Japanese managers. Specifically, the investigators use a regression discontinuity design to estimate the impacts of the purge on the firms whose managers were removed and on the firms to which these managers moved. The latter requires constructing a control group consisting of firms to which managers just below the cutoff would have plausibly transitioned had they been purged. This can be done by using archival data to estimate a model of manager transitions that includes rich individual, firm, and network level characteristics. This research also exploits the same plausibly exogenous variation to test whether managerial connections helped Taiwanese entrepreneurs to also transition into these industries.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

不同公司的工作效率、创新能力和过渡到新产品领域的能力差异很大。这些差异是理解经济发展和结构变化的核心，这项研究侧重于一个潜在的重要决定因素：管理资本。背景是战后的日本，这一背景既提供了大规模的自然实验，也提供了极其丰富的数据。在日本占领期间，盟军对日本大公司的高级管理人员进行了“经济清洗”。1937年至1945年间任何时候受雇于净资产超过1亿日元的公司的经理都将被强制免职，并被禁止在其他大公司担任管理职位。他们通常会转移到新兴行业的公司，这些行业并不是由大型企业集团主导的。整肃可能剥夺了日本大公司稀缺的人才，从而降低了经济表现，也可能为年轻、创新的领导者获得立足点扫清了道路。它还可以通过将人才引导到较新的、新兴的行业来促进创新，这些行业往往不受清洗的影响。然而，如果管理资本主要嵌入到组织规范中，而不是个人中，那么清洗的效果可能有限。这项研究通过将管理人员被清洗的公司与勉强避免清洗的公司进行比较，估计了清洗的影响。它还考察了被罢免的经理人跳槽到的公司的业绩。最后，对于那些在殖民台湾运营的分支机构的经理，报告考察了与前台湾员工的持续联系是否帮助这些员工随后过渡到与其前日本经理相关的行业。具体地说，调查人员使用回归不连续设计来估计清洗对经理被免职的公司和这些经理被转移到的公司的影响。后者需要建立一个由公司组成的控制组，如果经理被清洗，略低于下限的经理似乎会过渡到这些公司。这可以通过使用档案数据来估计经理过渡的模型来实现，该模型包括丰富的个人、公司和网络级特征。这项研究还利用同样看似合理的外生变量来测试管理联系是否帮助台湾企业家也过渡到这些行业。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

OLALA: Object-Level Active Learning Based Layout Annotation

• 发表时间: 2020-10
• 期刊: ArXiv
• 作者: Zejiang Shen;Jian Zhao;Melissa Dell;Yaoliang Yu;Weining Li

A Large Dataset of Historical Japanese Documents with Complex Layouts

• DOI: 10.1109/cvprw50498.2020.00282
• 发表时间: 2020-04
• 期刊: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
• 作者: Zejiang Shen;Kaixuan Zhang;Melissa Dell

Information Extraction from Text Regions with Complex Tabular Structure.

从具有复杂表格结构的文本区域中提取信息。

• 发表时间: 2019
• 期刊: Conference on Neural Information Processing Systems
• 作者: Zhang, Kaixuan;Shen, Zejiang;Zhou, Jie;Dell, Melissa
• 通讯作者: Dell, Melissa

LayoutParser: A Unified Toolkit for Deep Learning Based Document Image Analysis

• DOI: 10.1007/978-3-030-86549-8_9
• 发表时间: 2021-03
• 期刊: ArXiv
• 作者: Zejiang Shen;Ruochen Zhang;Melissa Dell;Benjamin Charles Germain Lee;Jacob Carlson;Weining Li