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Cited by 986Qualitative Research Methods and ApplicationsQualitative Research Methods and EthicsBusiness Strategies and Management Research

What Is Qualitative Research? An Overview and Guidelines

Open access
Lim, Weng Marc·2025·Australasian Marketing Journal
DOI 10.1177/14413582241264619
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Abstract

This guide explains the focus, rigor, and relevance of qualitative research, highlighting its role in dissecting complex social phenomena and providing in-depth, human-centered insights. The guide also examines the rationale for employing qualitative methods, underscoring their critical importance. An exploration of the methodology’s strengths, such as its ability to offer contextual depth and holistic perspectives, is juxtaposed against challenges like constrained generalizability and potential researcher bias, accompanied by practical mitigation strategies. Covering a spectrum of qualitative approaches, including grounded theory, phenomenology, ethnography, action research, and general inquiry, the guide sheds light on diverse data collection and analysis techniques. Noteworthily, the guide underscores the crucial aspect of trustworthiness in qualitative research, detailing methods to establish credibility, dependability, confirmability, and transferability. The integration of technologies like recording and transcribing tools with data analysis software and the growing influence of artificial intelligence, machine learning, and deep learning are also explored. Concluding with a discussion on ethical considerations, from participant recruitment to data stewardship, this guide serves as an essential resource that offers insightful, actionable guidance for conducting effective and impactful qualitative research.

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  • Qualitative assessment can be feasibly integrated into existing workflows, even with limited resources.

    “Drawing on current literature and recent case studies from academic libraries, this article demonstrates that qualitative assessment, though sometimes perceived as time-and labor-intensive, can be feasibly integrated into existing workflows, even with limited resources.”

    From Beyond Numbers (2025) · cites this paper as Lim, 2025

  • Qualitative methods are especially advantageous under resource constraints because they are adaptable, low-cost, and scalable.

    “Qualitative methods are especially advantageous under such conditions because they are adaptable, low-cost, and scalable (Kohler, 2024;Lim, 2025).”

    From Beyond Numbers (2025) · cites this paper as Lim, 2025

  • The study adopted a qualitative research design appropriate for exploring meanings, expectations, and interpretations rather than measuring frequencies or testing hypotheses.

    “This study adopted a qualitative research design, which is appropriate for exploring meanings, expectations, and interpretations rather than measuring frequencies or testing hypotheses (Lim, 2024).”

    From Use of artificial intelligence tools in the publishing process: expectations from publishers through author guidelines (2026) · cites this paper as Lim, 2024

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Authors
Lim, W. M.
Affiliations
Swinburne University of Technology (AU)
Corresponding author
Lim, Weng Marc
ORCID
Lim, Weng Marc
Venue
Australasian Marketing Journal
Publisher
SAGE Publications
Published
2024-07-25
Volume
33
Issue
2
Pages
199-229
ISSN
  • 1441-3582 (ISSN-L)
  • 1839-3349
DOI
10.1177/14413582241264619
OpenAlex
W4401036688
Cited by
985
References
67
Citations by year
2026: 553 · 2025: 392 · 2024: 40
FWCI
1234.85
Type
journal article
Language
en
Open access
Licence
Locations
Australasian Marketing Journal (AMJ) (publishedVersion, cc-by)
Topics
  • Social Sciences › Education › Qualitative Research Methods and Applications
  • Social Sciences › Sociology and Political Science › Qualitative Research Methods and Ethics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Business Strategies and Management Research
Keywords
qualitative research, grounded theory, phenomenology, ethnography, action research, trustworthiness, credibility, researcher bias, generalizability, data collection, data analysis, artificial intelligence in qualitative research, research ethics, data stewardship

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