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Cross-sectional research: A critical perspective, use cases, and recommendations for IS research

  • Christian Maier*
  • , Jason Bennett Thatcher
  • , Varun Grover
  • , Yogesh K. Dwivedi
  • *Corresponding author for this work

Research output: Contribution to journal › Editorial

336 Scopus citations

Abstract

Cross-sectional data is pervasive in information systems (IS) research. This editorial reviews cross-sectional studies, summarizes their strengths and limitations, and derives use cases of when cross-sectional data is and is not useful in answering research questions. We raise concerns about assertions of temporal causality using data collected employing cross-sectional methods with no temporal order, which makes cause and effect difficult to establish. Based on our discussion of research using cross-sectional data and its limitations, we offer four recommendations for when and how to use such data: (1) improve credibility by reporting research in detail and transparently, (2) ensure appropriate sampling, (3) take configurational perspectives, and (4) integrate cross-sectional data into mixed- or multi-method designs. By doing so, we help IS researchers position and use cross-sectional studies appropriately within their methodological repertoire.

Original languageEnglish
Article number102625
JournalInternational Journal of Information Management
Volume70
DOIs
StatePublished - Jun 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2023 Elsevier Ltd

Keywords

  • Causality
  • Cross-sectional research
  • Cross-sectional study design
  • Cross-sectional survey
  • Cross-sectional survey design
  • Survey
  • Survey research design

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Computer Networks and Communications
  • Information Systems and Management
  • Marketing
  • Library and Information Sciences
  • Artificial Intelligence

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