Cross-Sectional versus Longitudinal Survey Research: Concepts, Findings, and Guidelines

TLDR

Marketing scholars and practitioners often use cross‑sectional surveys, but editors, reviewers, and authors increasingly question their validity, especially regarding common method variance bias and causal inference, and view longitudinal data collection as a potential remedy. The article conceptually examines how longitudinal surveys can address these validity concerns and provides guidelines to help researchers decide when to use them. The authors illustrate the validity comparison by analyzing two datasets and running a Monte Carlo simulation. Their findings indicate that, under certain conditions, cross‑sectional data can yield validity comparable to longitudinal data, and they offer guidelines for researchers.

Abstract

Marketing academics and practitioners frequently employ cross-sectional surveys. In recent years, editors, reviewers, and authors have expressed increasing concern about the validity of this approach. These validity concerns center on reducing common method variance bias and enhancing causal inferences. Longitudinal data collection is commonly offered as a solution to these problems. In this article, the authors conceptually examine the role of longitudinal surveys in addressing these validity concerns. Then, they provide an illustrative comparison of the validity of cross-sectional versus longitudinal surveys using two data sets and a Monte Carlo simulation. The conceptualization and findings suggest that under certain conditions, the results from cross-sectional data exhibit validity comparable to the results obtained from longitudinal data. This article concludes by offering a set of guidelines to assist researchers in deciding whether to employ a longitudinal survey approach.