Intercoder Validation Dataset for Strategic Posture Coding of 10 NASDAQ-100 Firms (2024)

This dataset presents an intercoder validation exercise for Ansoff’s Strategic Posture framework, applied to a 2024 sample of ten NASDAQ-100 firms. The purpose is to assess inter-rater reliability in measuring strategic alignment across three coders with distinct evaluation profiles:

Coder A (aggressive): assigns higher turbulence (ETL ≈ 4.7) and emphasizes bold ratings for aligned firms, while moderating misaligned cases around 3.5.

Coder B (conservative): assigns lower turbulence (ETL ≈ 4.1) and uses a restrained mix of 3s and 4s, with few 5s, reflecting a cautious interpretation of strategic behavior.

Coder C (balanced): positioned between A and B, with ETL ≈ 4.6 and moderate ratings across aggressiveness and capability, providing a midpoint perspective.

Each coder independently rated 65 items per firm, drawn from the Optimal Strategic Performance Positioning (OSPP) diagnostic:

25 Environmental Turbulence (ETL) items,

20 Strategic Aggressiveness (SA) items,

20 Capability Responsiveness (CR) items.

Ratings are provided on a 1–5 Likert scale, anchored to observable firm behaviors and industry conditions. The ten firms include both strategically aligned exemplars (e.g., Apple, Microsoft, Amazon, Tesla, Costco) and misaligned cases (e.g., PayPal, Warner Bros. Discovery, Biogen, Kraft Heinz, Charter Communications).

The dataset is organized in a single Excel file with three sheets:

CODER_RATINGS – Long format item-level data (1,950 rows = 3 coders × 10 firms × 65 items).

SUMMARY – Coder-firm means for ETL, SA, and CR, including alignment gaps (SA–ETL, SA–CR) and a simple posture score (X₁ average).

METADATA – Documentation of coder profiles, coding logic, and data dictionary.

This dataset enables reproducibility of intercoder reliability metrics (e.g., Krippendorff’s α, ICC), robustness checks of posture measurement, and sensitivity analyses of gap-based alignment scores. It complements the primary study on Ansoff’s Strategic Success Hypothesis by directly addressing methodological concerns about single-coder designs and demonstrating transparency in the coding process.

All data are based on publicly available firm disclosures, industry reports, and observable strategic actions for 2024. No confidential or proprietary information was used.