While multiple time-series analysis (MTSA) is a well-established method in economics, marketing, and finance, few studies have applied MTSA in organizational research. With the growing availability of data sources that contain detailed time-series data and the increasing importance of longitudinal designs, we argue that MTSA blends well with organizational research. We exemplify the possible applications of MTSA to the topics of social media, innovation, ambidexterity, and top management teams. We illustrate the state-of-the-art MTSA technique – Vector Autoregressive (VAR) model – by explaining the key methodological steps needed to estimate and interpret the results and providing a software tutorial in R and STATA. In line with the rising popularity of social media data, we employ a dataset that combines public social media data from Facebook with corporate reputation data from a private data source. We conclude with a discussion on the applicability, limitations, and extensions of MTSA for academics and practitioners.

虽然多重时间序列分析 (MTSA) 在经济学、市场营销和金融领域是一种成熟的方法，但很少有研究将 MTSA 应用于组织研究。随着包含详细时间序列数据的数据源的日益普及以及纵向设计的重要性日益增加，我们认为 MTSA 与组织研究很好地融合在一起。我们举例说明了 MTSA 在社交媒体、创新、二元性和高层管理团队等主题上的可能应用。我们通过解释估计和解释结果所需的关键方法步骤并提供 R 和 STATA 软件教程来说明最先进的 MTSA 技术 - 矢量自回归 (VAR) 模型。随着社交媒体数据的日益普及，我们使用了一个数据集，该数据集将来自 Facebook 的公共社交媒体数据与来自私人数据源的企业声誉数据相结合。最后，我们讨论了 MTSA 对学者和从业者的适用性、局限性和扩展性。