Multiple Time Series Analysis for organizational research

Colicev, Anatoli ORCID: 0000-0002-3311-8334 and Pauwels, Koen (2022) Multiple Time Series Analysis for organizational research. LONG RANGE PLANNING, 55 (2). p. 102067. ISSN 0024-6301, 1873-1872

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Abstract

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.

Item Type:	Article
Uncontrolled Keywords:	Time -series econometrics, Vector auto -regression, Organizational research, Applied guidelines, Social media data, Corporate reputation
Divisions:	Faculty of Humanities and Social Sciences Faculty of Humanities and Social Sciences > School of Management
Depositing User:	Symplectic Admin
Date Deposited:	07 Oct 2024 13:11
Last Modified:	06 Dec 2024 20:11
DOI:	10.1016/j.lrp.2020.102067
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3184916