Emotional intelligence and engagement

Problem. Work engagement has emerged as a central construct in organizational psychology, yet research on its antecedents has relied predominantly on net-effect models that assume emotional competencies operate in compensatory, additive ways. Whether specific emotional intelligence (EI) dimensions function as non-compensatory necessary conditions — thresholds below which engagement cannot emerge regardless of other resources — remains largely unexplored, constraining both theoretical development and evidence-based human resource development (HRD) practice. Solution. This study integrates Partial Least Squares Structural Equation Modeling (PLS-SEM) and Necessary Condition Analysis (NCA) to examine the predictive and necessary-condition roles of five EI dimensions on work engagement among employees of a Brazilian credit cooperative. Emotional intelligence explained 51.0% of engagement variance. Stakeholders. HRD scholars, organizational leaders, HR managers, and practitioners interested in EI development and work engagement will benefit from the differentiated typology of EI dimensions derived from the integrative PLS-SEM–NCA framework.问题。工作投入已成为组织心理学中的核心构念，但现有关于其前因的研究大多依赖净效应模型，这类模型假定情绪能力以补偿性、累加性的方式发挥作用。特定情绪智力（Emotional Intelligence, EI）维度是否以非补偿性必要条件的形式发挥作用——即当该维度水平低于某一阈值时，无论其他资源状况如何，工作投入均无法产生——这一问题迄今仍未得到充分探索，进而制约了理论发展与循证人力资源开发（Human Resource Development, HRD）实践。 解决方案。本研究结合偏最小二乘结构方程模型（Partial Least Squares Structural Equation Modeling, PLS-SEM）与必要条件分析（Necessary Condition Analysis, NCA），针对巴西某信贷合作社的员工群体，检验了五个情绪智力维度对工作投入的预测作用与必要条件作用。研究结果表明，情绪智力可解释51.0%的工作投入变异量。 利益相关方。对情绪智力开发与工作投入主题感兴趣的人力资源开发（Human Resource Development, HRD）学者、组织管理者、人力资源经理及实务从业者，将从本研究整合偏最小二乘结构方程模型-必要条件分析框架所得到的情绪智力维度差异化类型学中获益。