Integrated UET–Strategic Posture Panel Dataset for NASDAQ Firms (2006–2015)

This dataset integrates Upper Echelons Theory (UET) variables with Ansoff’s Strategic Posture framework to examine the relationship between executive characteristics, strategic calibration, and firm outcomes. It provides a structured firm-year panel for 25 NASDAQ-listed firms over the period 2006–2015.
The dataset combines three components. First, strategic posture and performance variables are drawn from the author’s doctoral research (Bonelli, 2017), including a composite posture score (X1), internal structure (X2), an observed alignment differential (Diff), short-term operating growth, and analyst-based estimated growth. These variables are based on Ansoff’s Optimal Strategic Performance Positioning (OSPP) framework.
Second, the dataset incorporates a hand-coded executive layer based on publicly available disclosures. Executive variables include CEO duality, founder status, a composite power index, insider versus outsider succession, CEO tenure, functional background, technical orientation, and industry familiarity. Coding is conducted using a structured protocol informed by Upper Echelons Theory and the CUP-W analytical framework, relying on annual reports, proxy statements, and investor relations materials.
Third, the dataset includes derived subsets to support empirical analysis, including a main estimation sample, a balanced panel subset, and a transition subset capturing CEO changes. A separate validation component based on a 2024 intercoder dataset is included for measurement support but is not part of the main estimation panel.
The purpose of this dataset is to enable multi-level analysis linking executive structure to strategic posture and firm performance. It supports models testing whether executive characteristics are associated with strategic calibration and whether posture acts as an intermediate mechanism connecting upper echelons to firm outcomes.
The dataset is suitable for replication, extension, and methodological research in strategic management, corporate governance, and behavioral finance. It provides a transparent and reproducible framework for studying how executive attributes are reflected in firm-level strategic behavior and performance dynamics.

本数据集整合了高层梯队理论（Upper Echelons Theory, UET）变量与安索夫战略姿态框架（Ansoff’s Strategic Posture framework），旨在考察高管特征、战略校准与企业绩效三者间的关联。数据集提供了2006-2015年间25家纳斯达克（NASDAQ）上市企业的结构化企业年度面板数据。
本数据集包含三大组成部分。其一，战略姿态与绩效变量源自作者的博士研究（Bonelli, 2017），包括综合姿态得分（X1）、内部结构（X2）、观测对齐偏差（Diff）、短期运营增长以及基于分析师估算的增长；上述变量均基于安索夫最优战略绩效定位（Ansoff’s Optimal Strategic Performance Positioning, OSPP）框架构建。其二，数据集纳入了基于公开披露信息手工编码的高管层数据，高管变量涵盖两职合一（CEO duality）、创始人身份、综合权力指数、内部继任与外部继任、CEO任期、职能背景、技术导向及行业熟悉度。编码工作遵循依托高层梯队理论与CUP-W分析框架制定的结构化协议，依托年度报告、委托书声明及投资者关系材料完成。其三，数据集包含支撑实证分析的衍生子集，包括主估计样本、平衡面板子集以及捕捉CEO变更的转型子集；此外还纳入了基于2024年编码员间数据集的独立验证组件，用于辅助测量，但该组件不属于主估计面板。
本数据集的核心目标是支持将高管结构与战略姿态、企业绩效相联结的多层面分析，可用于检验两类研究模型：一是高管特征是否与战略校准存在关联，二是战略姿态是否作为中介机制连接高层梯队与企业绩效。
本数据集适用于战略管理、公司治理及行为金融领域的重复研究、拓展研究与方法论研究，可为探究高管属性如何映射至企业层面的战略行为与绩效动态提供透明且可复现的研究框架。