Multiple Time Series Analysis for Organizational Research

51 Pages Posted: 13 Jan 2019

Date Written: December 16, 2018

Abstract

Temporal dynamics have become highly relevant across social sciences both for theory and practice. While multiple time-series analysis (MTSA) is designed to analyze temporal dynamics, few studies so far have used MTSA in organizational research. Possible reasons include the perceived absence of fit between MTSA and organizational research topics, predominance of cross-sectional designs due to difficulty in collecting time-series data and a lack of guidelines on applying MTSA. We argue that MTSA blends well with research topics that deal with temporal dynamics ranging from strategic change and ambidexterity to social media and corporate social responsibility. Thus, the aim of this article is to provide a relatively nontechnical introduction to MTSA. We illustrate the state-of-the-art MTSA technique – Vector Autoregressive (VAR) model – by explaining the key methodological steps needed to correctly estimate and interpret the results from such models. To illustrate the methodology, we employ a dataset that combines social media and corporate reputation. Finally, we provide a discussion on applicability, limitations and extensions of MTSA for academics and practitioners as well as a software tutorial in R and STATA.

Suggested Citation

Colicev, Anatoli and Pauwels, Koen H., Multiple Time Series Analysis for Organizational Research (December 16, 2018). Available at SSRN: https://ssrn.com/abstract=3302191 or http://dx.doi.org/10.2139/ssrn.3302191

Anatoli Colicev (Contact Author)

Bocconi University ( email )

Via Sarfatti, 25
Milan, MI 20136
Italy

Koen H. Pauwels

Ozyegin University ( email )

Kusbakisi Cd. No: 2
Altunizade, Uskudar
Istanbul, 34662
Turkey

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