Orchestration Log: When this skill is activated, append a log entry to outputs/orchestration_log.md:
```
### Skill Activation: Method Engine
Timestamp: [current date/time]
Actor: AI Agent (method-engine)
Input: [brief description of the methodology request]
Output: [brief description of what was produced — e.g., "DSR method section drafted with 3 evaluation criteria"]
```
Method Engine
Method Selection Guide
Decision Tree
What is your primary research goal?
│
├─ "I want to map what the literature says"
│ → Systematic Literature Review (Section A)
│
├─ "I want to understand a phenomenon in depth"
│ → Qualitative Study (Section B)
│ ├─ Single context, deep → Single Case Study
│ ├─ Multiple contexts, comparison → Multiple Case Study
│ ├─ Build new theory from data → Grounded Theory / Gioia
│ └─ Analyze text/documents systematically → Content Analysis (Mayring)
│
├─ "I want to test hypotheses / measure relationships"
│ → Quantitative Study (Section C)
│ ├─ Complex model with latent variables → SEM (PLS or CB)
│ ├─ Simpler relationships → Regression
│ └─ Experimental comparison → Experiment / RCT (Section F)
│
├─ "I want to build something (tool, framework, model)"
│ → Design Science Research (Section D)
│
├─ "I want to combine approaches"
│ → Mixed Methods (Section E)
│
├─ "I want to improve practice through iterative intervention"
│ → Action Research (Section G)
│
├─ "I want to understand culture, practices, or lived experience"
│ → Ethnography (Section H)
│
├─ "I want structured expert consensus on a complex issue"
│ → Delphi Study (Section I)
│
└─ "I want to model and test scenarios computationally"
→ Simulation (Section J)Section A: Systematic Literature Review
Method Section Template (ready to adapt):
3. Research Methodology
We conducted a systematic literature review following the guidelines of
[vom Brocke et al. (2009, 2015) / Webster & Watson (2002) / Kitchenham &
Charters (2007) / PRISMA 2020 (Page et al., 2021)]. This approach is
appropriate because [justification: need to synthesize a growing but
fragmented body of knowledge / field is maturing and needs stock-taking /
practical guidance requires evidence synthesis].
3.1 Search Strategy
We searched [N] electronic databases: Semantic Scholar, OpenAlex, CrossRef,
[and arXiv for preprints / and AIS eLibrary for IS-specific venues].
The search was conducted in [month/year] using the following query terms:
[("generative AI" OR "generative artificial intelligence" OR "large language
model*" OR "LLM" OR "GPT" OR "foundation model*") AND ("enterprise" OR
"organization*" OR "business" OR "implementation" OR "adoption")]
[("AI agent*" OR "autonomous agent*" OR "agentic AI") AND ("organization*"
OR "enterprise" OR "business process" OR "implementation")]
The search was limited to publications from [year] to [year], in
[English / English and German].
3.2 Selection Criteria
Table [N] summarizes our inclusion and exclusion criteria.
| ID | Criterion | Rationale |
|----|-----------|-----------|
| IC1 | Peer-reviewed journal article or conference paper | Quality assurance |
| IC2 | Focuses on [topic] in organizational context | Scope alignment |
| IC3 | Published between [year] and [year] | Recency |
| IC4 | Available in English [or German] | Accessibility |
| EC1 | Purely technical (no organizational dimension) | Out of scope |
| EC2 | Editorial, book review, or abstract-only | Insufficient depth |
| EC3 | Duplicate publication | Avoid double-counting |
3.3 Search and Screening Process
Figure [N] presents the PRISMA flow diagram of our search and selection process.
The initial search yielded [N] records across all databases. After removing
[N] duplicates, [N] records were screened based on title and abstract, of
which [N] were excluded. The remaining [N] articles were assessed in full text,
resulting in [N] studies included in the final synthesis.
[Forward and backward citation tracking (snowballing) on the [N] most-cited
included studies identified an additional [N] relevant papers, bringing the
total to [N] studies.]
3.4 Data Extraction and Analysis
From each included study, we extracted: [list categories: research question,
theoretical lens, methodology, sample/context, key findings, limitations,
and contribution type].
We synthesized findings using a concept-centric approach (Webster & Watson, 2002),
organizing results in a concept matrix that maps studies against key themes
identified through iterative reading and coding.PRISMA Flow Diagram (text version):
Identification:
Records from Semantic Scholar: [n]
Records from OpenAlex: [n]
Records from CrossRef: [n]
Records from arXiv: [n]
Records from manual/snowballing: [n]
─────────────────────────────────
Total identified: [N]
Duplicates removed: -[n]
Records after deduplication: [N]
Screening:
Title/abstract screened: [N]
Excluded: -[n]
Full-text assessed: [N]
Eligibility:
Full-text excluded (with reasons): -[n]
- Not organizational context: [n]
- Not empirical/conceptual: [n]
- Not accessible: [n]
Included:
Studies in final synthesis: [N]Section B: Qualitative Methods
Case Study (Yin, 2018 / Eisenhardt, 1989)
Method section template:
3. Research Methodology
We employed a [single/multiple] case study approach (Yin, 2018) to investigate
[phenomenon] in [context]. Case study research is appropriate when investigating
a contemporary phenomenon within its real-world context, particularly when the
boundaries between phenomenon and context are not clearly evident (Yin, 2018).
3.1 Case Selection
[For single case:] We selected [case] as a [revelatory/critical/typical/extreme]
case (Yin, 2018) because [justification].
[For multiple cases:] Following [theoretical/literal] replication logic
(Yin, 2018), we selected [N] cases based on [selection criteria]. Table [N]
provides an overview of the cases.
| Case | Industry | Size | AI Maturity | Selection Rationale |
|------|----------|------|-------------|---------------------|
| A | [X] | [X] | [X] | [X] |
| B | [X] | [X] | [X] | [X] |
3.2 Data Collection
We collected data from multiple sources to enable triangulation (Yin, 2018):
- [N] semi-structured interviews with [roles] (average duration: [X] minutes)
- Internal documents: [list types]
- [Observation / workshop protocols / system logs]
- [Archival data: annual reports, press releases]
All interviews were recorded and transcribed [verbatim / in summary form].
3.3 Data Analysis
We analyzed the data using [thematic analysis (Braun & Clarke, 2006) /
the Gioia methodology (Gioia et al., 2013) / qualitative content analysis
(Mayring, 2014)]. [Method-specific description — see subsections below.]
3.4 Research Quality
We ensured research quality through:
- **Construct validity**: Multiple data sources, chain of evidence
- **Internal validity**: Pattern matching, explanation building
- **External validity**: [Replication logic across cases / analytical generalization]
- **Reliability**: Case study protocol, case study databaseGioia Methodology (Gioia et al., 2013)
Data analysis followed the Gioia methodology (Gioia et al., 2013). First, we
engaged in open coding of interview transcripts and documents, identifying
first-order concepts that remained close to informant language. This yielded
[N] initial codes. Through constant comparison and iterative abstraction, we
grouped these into [N] second-order themes reflecting more abstract,
researcher-driven categories. Finally, we aggregated themes into [N]
overarching dimensions that form the basis of our emerging framewo