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.本数据集为安索夫战略态势框架（Ansoff’s Strategic Posture framework）的编码者间验证练习数据集，应用于2024年选取的10家纳斯达克100（NASDAQ-100）成分股企业样本。本研究旨在评估三名具备不同评估特征的编码者在衡量战略契合度时的编码者间信度。 三名编码者的评估特征如下： 编码者A（激进型）：赋予更高的环境动荡水平（Environmental Turbulence, ETL≈4.7），并对战略契合的企业给出较高评分，而对不契合的案例评分则维持在3.5左右。 编码者B（保守型）：赋予较低的环境动荡水平（ETL≈4.1），评分以克制的3分和4分组合为主，极少使用5分，体现出对战略行为的审慎解读。 编码者C（均衡型）：评分介于A与B之间，ETL≈4.6，在攻击性与能力响应性维度均给出中等评分，提供了中立视角。 每名编码者独立对每家企业的65个条目进行评级，数据源自最优战略绩效定位（Optimal Strategic Performance Positioning, OSPP）诊断工具，包含三类条目：25项环境动荡水平（ETL）条目、20项战略攻击性（Strategic Aggressiveness, SA）条目以及20项能力响应性（Capability Responsiveness, CR）条目。 评级采用1-5李克特（Likert）量表，锚定可观测的企业行为与行业环境。10家样本企业既包括战略契合的标杆企业（如苹果（Apple）、微软（Microsoft）、亚马逊（Amazon）、特斯拉（Tesla）、好市多（Costco）），也包含战略不契合的案例（如贝宝（PayPal）、华纳兄弟探索（Warner Bros. Discovery）、渤健（Biogen）、卡夫亨氏（Kraft Heinz）、特许通讯（Charter Communications））。 本数据集以单个Excel文件存储，包含三个工作表： 1. CODER_RATINGS：长格式条目级数据（共1950行，即3名编码者×10家企业×65个条目）； 2. SUMMARY：各编码者对每家企业的ETL、SA、CR维度均值，包含契合缺口（SA–ETL、SA–CR）以及简易态势得分（X₁平均值）； 3. METADATA：编码者特征说明、编码逻辑与数据字典文档。 本数据集可复现编码者间信度指标（如克里彭多夫α系数（Krippendorff’s α）、组内相关系数（ICC）），支持态势测量的稳健性检验，以及基于缺口的契合得分敏感性分析。本数据集补充了安索夫战略成功假说的相关研究，直接回应了单编码者设计的方法论顾虑，并展现了编码流程的透明度。 所有数据均基于2024年公开的企业披露信息、行业报告与可观测的战略行动，未使用任何保密或专有信息。