联盟
匹配(统计)
分类学(生物学)
序列(生物学)
集合(抽象数据类型)
透视图(图形)
聚类分析
知识管理
知识获取
业务
计算机科学
人工智能
生物
政治学
生态学
数学
统计
程序设计语言
法学
遗传学
作者
Weilei Shi,John E. Prescott
标识
DOI:10.1111/j.1467-6486.2010.00953.x
摘要
abstract Studying repetitive acquisition and alliance behaviours from a temporal perspective, we conceptualize a taxonomy of sequence patterns. Our approach defines sequences as the set of acquisition and alliances a firm initiates each year over its life‐course. Using optimal matching techniques and clustering analysis, we empirically identify seven different sequence patterns and demonstrate that firm and performance attributes differ across these sequences and depending on the contingent effect of a firm's stage of development. We discuss the implications of our taxonomy and findings for our understanding of the temporal management of alliance portfolios and acquisition programmes.
科研通智能强力驱动
Strongly Powered by AbleSci AI