发表机构
Elon University; Signalead LLC（埃隆大学; Signalead有限责任公司）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究开发并验证了AI领导力电池，一个包含36个子维度和11个内容族的多维测量工具，用于评估AI赋能组织中领导者的判断、学习、适应、透明与问责行为。
AI 中文摘要
AI正在改变领导者必须判断、解释、学习和协调的内容，然而现有测量工具无法在AI赋能工作背景下以研究领导力所需的粒度捕捉这些行为。我们开发了AI领导力电池（AI Leadership Battery），将36个行为特定的子维度组织为11个理论指定的内容族。遵循既定的量表开发程序，本研究采用了演绎式条目生成；对定义对应性和定义区分性进行内容验证；探索性因子分析与条目精简；在独立样本中进行验证性因子分析；以及内部一致性信度、收敛效度、区分效度、效标关联效度和增量效度的检验。在开发与验证研究中，分析结果为该电池的内容效度、多维结构、信度及其与所选邻近构念的区分提供了证据。该电池还在组织成长、决策速度、客户/利益相关者响应能力、AI赋能团队绩效、AI赋能工作体验、AI安全与风险管理以及AI采纳与整合等方面，提供了超越邻近构念的额外信息。最终形成的测量工具为研究者提供了一个行为框架，用以考察AI赋能工作中的领导者如何调节判断、学习、适应、透明度和问责。
英文摘要
AI is changing what leaders must judge, explain, learn, and coordinate, yet existing measures do not capture these behaviors at the level needed to study leadership in AI-enabled work. We develop the AI Leadership Battery, which organizes 36 behaviorally specific subdimensions into 11 theory-specified content families. Following established scale-development procedures, the research used deductive item generation; content validation of definitional correspondence and definitional distinctiveness; exploratory factor analysis and item reduction; confirmatory factor analysis in independent samples; and tests of internal consistency reliability, convergent validity, discriminant validity, and criterion-related and incremental validity. Across the development and validation studies, the analyses provided evidence for the Battery's content, multidimensional structure, reliability, and distinction from selected orbiting constructs. The Battery also contributed additional information beyond orbiting constructs across organizational growth, decision speed, customer/stakeholder response capability, AI-enabled team performance, AI-enabled work experience, AI security and risk management, and AI adoption and integration. The resulting measure provides researchers with a behavioral framework for examining how leaders in AI-enabled work regulate judgment, learning, adaptation, transparency, and accountability.
