UNDERSTANDING THE ALLIANCE DATA

• 成果类型: Article
• 署名作者: Schilling, Melissa A.
• 署名单位: New York University
• 刊物名称: STRATEGIC MANAGEMENT JOURNAL
• ISSN/ISSBN: 0143-2095
• DOI: 10.1002/smj.731
• 发表日期: 2009
• 页码: 233-260
• 关键词: alliances; joint ventures; methodology; networks; sampling theory

摘要

A considerable body of research utilizes large alliance databases (e.g., SDC, MERIT-CATI, CORE, RECAP, and BIOSCAN) to study interorganizational relationships. Understanding the strengths and limitations of these databases is crucial for informing database selection and research design. In this study I conduct an analysis of five prominent alliance databases. Focusing on technology alliances (those,formed for the purposes of joint research or cross-technology transfer), I examine the databases' consistency (of coverage and completeness, and assess whether different databases yield the same patterns in sectoral composition, temporal trends, and geographic patterns in alliance activity. I also replicate three previously published alliance studies to assess the impact of data limitations on research outcomes. The results suggest that the databases only report a fraction of formally), announced alliances, which could have detrimental consequences for some types of research. However, the databases exhibit strong symmetries in patterns of sectoral composition, alliance activity over time, and geographic participation. Furthermore, the replications of previous studies yielded results that were highly similar to those obtained in the original studies. This study thus provides some reassurance that even though the databases only capture a sample of alliance activity, they may yield reliable results for many-if not all-research purposes. This information should help researchers make better-informed decisions about their choice of database and research design. Copyright (C) 2008 John Wiley & Sons, Ltd.