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Andy Weeger / Neu-Ulm University of Applied Sciences Neu-Ulm

Some thoughts on SLRs
in IS and beyond

Goals, types, inductive analysis and the role of GenAI

Andy Weeger

Neu-Ulm University of Applied Sciences

July 4, 2025

Introduction

Why structured literature reviews (SLRs)?

An effective review creates a firm foundation for advancing knowledge. It facilitates theory development, closes areas where a plethora of research exists, and uncovers areas where research is needed. (Webster & Watson, 2002, p. xiii)

SLRs help to deal with the complexity and volume of research, and support the generation of new insights, methods, or theories.

Prime example in IS

Vial (2021) reviewed 282 studies on digital transformation using a rigorous five-step methodology based on that of Wolfswinkel et al. (2013)

Using a SLR, he:

  • synthesized fragmented research across multiple databases,
  • developed the first comprehensive conceptial defintion of DT,
  • inductively developed a novel theoretical framework on DT,
  • and proposed a research agenda.

The study had quite an impact in IS and beyond …

Impact

Goals of SLR

Four primary goals of literature reviews:

Goal Description Example from Vial (2019)
Describe Map the field, categorize literature Catalogue of 282 DT works across outlets
Understand Interpret phenomena and uncover patterns Comprehensive definition and 8 building blocks
Explain Develop or extend theoretical understanding Novel process framework on DT (main goal)
Test Assess the aggregated evidence —

Types of literature reviews

Distribution of goals and related review types in the top-tier IS journals from 2000 to 2014 according to Templier & Pare (2018):

Goal Review Type Total %
Describe Narrative review 25 18
Descriptive review 22 16
Understand Scoping review 9 6
Critical review 16 11
Explain Theory development review 52 37
Test Meta-analysis 12 8
Qualitative systematic review 6 4
Table 1: Types of review articles in the top-tier IS journals (EJIS, ISJ, ISR, JAIS, JIT, JMIS, JSIS, and MISQ) (Templier & Pare, 2018)

Phases of an SLR

Four-phase process:

  1. DESIGN — domain familiarization, identifying SLR need, prepare protocol
  2. DISCOVER — systematic search & selection strategy
  3. DEVELOP – quality assessment, data extraction, synthesis
  4. DISSEMINATE – transparent reporting and communication

Key Principles:
Systematic + Transparent = Trustworthy

But with varying degrees of rigor/structure …

Key differences accross phases

Phase Most structured Moderately structured Least structured
DESIGN Meta-analysis: formal protocols; pre-registration; precise hypotheses Scoping & critical reviews: comprehensive protocols, structured planning Narrative & theory development: most ‘flexible’/informal approach
DISCOVER Meta-analysis & scoping: exhaustive search, multiple databases Critical & qualitative systematic: systematic but targeted, multiple sources Theory development & narrative: selective search, quality over quantity
DEVELOP Meta-analysis: rigorous quality assessment, statistical synthesis, standardized extraction Scoping & critical: systematic analysis, quality screening, structured synthesis Theory development: concept-based extraction, interpretive analysis
DISSEMINATE Meta-analysis: PRISMA compliance, statistical reporting Scoping & qualitative systematic: good methodology reporting, clear documentation Narrative & theory development: focus on content over process
Table 2: Key differences of literature review types across phases (own summary based on Rowe (2014), Templier & Paré (2017), and Templier & Pare (2018))

Focus #1: Inductive qualitative analysis

Qualitative synthesis to develop explanations

Goal: Moving beyond mere aggregation to theory building.

From collecting and categorizing findings (aggregation)
to creating new theoretical insights from patterns (synthesis)
by means of structured inductive coding

Structured inductive coding

Coding structure based on Gioia methodology (Gioia et al., 2013)

Start with 1st-order concepts (data-driven)

  • Direct evidence from literature
  • Preserve original authors’ terminology and findings

Synthesize 2nd-order themes (interpretation)

  • Refine into higher-order categories
  • Identify theoretical concepts that explain patterns

Create aggregate dimensions (higher-level constructs)

  • Integrate relationships into framework
  • Create overarching theoretical framework

Example: Vial (2019)

From raw data extracted from exsiting research to novel theoretical framework for DT

Concept (literature findings)

  • “Digital technologies alter consumer behavior”
  • “Platforms enable new business models” …

Themes (analytical lense)

  • “Use of digital technologies”
  • “Disruptions”
  • “Strategic responses” …

Dimensions and relationships

Digital technologies fuel disruptions trigger strategic responses rely on digital technologies enable changes in value creation paths

Focus #2: GenAI in SLRs

Paradigm

Instead of discussing what Gen.AI can and cannot do, we should to discuss what we should allow Gen.AI to do.

Tingelhoff et al. (2024, p. 78)

GenAI use by SLR phase

Phase Key benefits Key risks Overall recommendation
DESIGN Enhanced comprehension, processing capabilities, alignment with standards Potential biases, over-reliance on existing narratives Use as starting point and for initial suggestions; maintain researcher control over core decisions
DISCOVER Broadened scope, uncovered connections, enhanced comprehensiveness Biases affecting integrity and transparency, over-reliance on prevailing narratives Use supplementarily for initial discovery; always cross-reference and supplement with manual methods
DEVELOP Streamlined analysis, pattern identification, enhanced efficiency Lack of transparency, biases might undermine reproducibility Use for initial analysis and pattern identification; verify manually and keep core synthesis researcher-led
DISSEMINATE Improved clarity in writing, increased impact Undermining integrity & responsibility (misuse) Use only for refining language and clarity; avoid AI-generated content
Table 3: Benefits, risks and recommendations based on Tingelhoff et al. (2024)

Critical safeguards

Tool-task fit: match GenAI capabilities to specific SLR needs

Triangulation: use multiple tools (similar to data source triangulation in traditional research)

Transparency: document all GenAI usage (essential for reproducibility and methodological rigor)

There are no shortcuts to making scientific contributions.

However, you can leverage the capabilities of GenAI while maintaining your human insight and scholarly rigor.

Summary

Key Takeaways

  • SLRs are foundational for systematic knowledge building
  • Inductive coding provides structured approach to qualitative synthesis
  • Three-level structure enables progression from data to theory
  • GenAI integration should be criteria-driven and transparent
  • Human judgment remains paramount for theoretical development

Literature

Gioia, D. A., Corley, K. G., & Hamilton, A. L. (2013). Seeking qualitative rigor in inductive research: Notes on the gioia methodology. Organizational Research Methods, 16(1), 15–31. https://doi.org/10.1177/1094428112452151
Rowe, F. (2014). What literature review is not: Diversity, boundaries and recommendations. European Journal of Information Systems, 23(3), 241–255. https://doi.org/10.1057/ejis.2014.7
Templier, M., & Pare, G. (2018). Transparency in literature reviews: An assessment of reporting practices across review types and genres in top IS journals. European Journal of Information Systems, 27(5), 503–550.
Templier, M., & Paré, G. (2017). Transparency in literature reviews: An assessment of reporting practices across review types and genres in top IS journals. European Journal of Information Systems. https://doi.org/10.1080/0960085X.2017.1398880
Tingelhoff, F., Brugger, M., & Leimeister, J. M. (2024). A guide for structured literature reviews in business research: The state-of-the-art and how to integrate generative artificial intelligence. Journal of Information Technology, 40(1), 77–99. https://doi.org/10.1177/02683962241304105
Vial, G. (2021). Understanding digital transformation: A review and a research agenda. Managing Digital Transformation, 13–66.
Webster, J., & Watson, R. T. (2002). Analyzing the past to prepare for the future: Writing a literature review. MIS Quarterly, xiii–xxiii.
Wolfswinkel, J. F., Furtmueller, E., & Wilderom, C. P. (2013). Using grounded theory as a method for rigorously reviewing literature. European Journal of Information Systems, 22(1), 45–55.

Thx for listening.

I am ready for a Q&A.

— andy.weeger@hnu.de