The Work of Organization and the Organization of Work: Mapping the Evolving Structure of Biotechnology

该项目继续研究生物技术产业的起源和发展。 这项研究的重点是各种新颖形式的合作安排，将大学、研究所、风险投资公司、老牌化学和制药公司以及研究医院与专门从事生物技术发现商业化的新的科学创业公司联系起来。 特别是，我们的研究测试的想法，当知识和技能广泛分布，创新的轨迹是在一个网络的组织间的关系。 为了在快速发展的科学领域保持领先地位，需要一个组织参与研究过程。 内部研究能力对于评估其他地方所做研究的质量和吸引主要合作伙伴至关重要，而外部合作则提供了获得内部无法产生的新闻和资源的机会。 我们认为，研究突破是通过来自不同科学领域和机构背景的参与者之间的密切互动而实现的。 为了测试这些想法，我们已经组装了一个关系数据库，使我们能够检查生物技术的合作模式。 根据行业参考来源，Bioscan，年度报告，美国证券交易委员会提交的文件和其他参考来源，我们编制了一份由专门的生物技术公司在人类治疗和诊断领域所签订的正式合同协议的记录。 本研究将使用这些数据来研究这些公司之间的高速学习和合作。 为此，我们将继续对各组织之间的关系进行网络分析，并将增加基于面对面访谈的定性材料以及其他定量分析

This project continues a line of research into the origins and development of the biotechnology industry. The focus of that research has been on the varied and novel forms of collaborative arrangements that have linked universities, research institutes, venture capital firms, established chemical and pharmaceutical corporations and research hospitals with new science-based startup companies specializing in commercializing biotech discoveries. In particular, our research tests the idea that, when knowledge and skills are widely distributed, the locus of innovation is found in a network of interorganizational relationships. To stay current in a rapidly-developing scientific field requires that an organization have a hand in the research process. Internal research capability is essential to evaluate the quality of research done elsewhere and to attract premier partners, while external collaboration provides access to news and resources that cannot be generated internally. In our view, research breakthroughs occur through intensive interaction among participants from diverse scientific fields and institutional contexts. To test these ideas, we have assembled a relational data base that allows us to examine patterns of collaboration in biotechnology. Drawing on an industry reference source, Bioscan, annual reports, Security and Exchange Commission filings, and other reference sources, we have compiled a record of the formal, contractual agreements undertaken by dedicated biotech firms in the human therapeutics and diagnostics field. The present study will use these data to examine high-speed learning and collaboration among such firms. To do this we will continue our network analyses of relations among organizations, and will add qualitative material based on face-to-face interviews as well as other quantitative analyses