Not Me,But Reflects Me: Validating a Simple Implicit Measure of Psychological Capital

We propose the recently introduced implicit measure of psychological capital (PsyCap), the Implicit Psychological Capital Questionnaire (I-PCQ; Harms & Luthans, 2012), can provide a needed valid alternative to the self-report Psychological Capital Questionnaire (PCQ). We explain the development of the I-PCQ items, assess the structural validity of the instrument, test its vulnerability to response distortion, and assess its capacity to predicting work attitudes and behaviors vis-à-vis the PCQ and Big Five personality facets. We found that the I-PCQ demonstrated acceptable structural validity that was consistent with and added to prior theorizing, was resistant to response distortion, and predicted work outcomes above and beyond the widely used self-report PCQ and Big Five personality traits. We conclude that the I-PCQ represents a valid, easily administered measure of psychological capital that minimizes problems associated with self-reports and is appropriate for use in work settings.     

Just the two of us: misalignment of theory and methods in examining dyadic phenomena

Many organizational phenomena such as leader-member exchange, mentoring, coaching, interpersonal conflict and cooperation, negotiation, performance appraisal, and the employment interview involve inherently dyadic relationships and interactions. Even when theories explicitly acknowledge the dyadic nature of such phenomena, it is not uncommon to observe a disconnection or misalignment between the level of theory and method. Our purpose in the current paper is to discuss how organizational scholars might better align these components of their research endeavors. We discuss how recent developments involving the actor-partner interdependence model (APIM) and reciprocal one-with-many (OWM) models are applicable to studying dyadic phenomena in organizations. The emphasis is on preanalytic considerations associated with collecting and organizing reciprocal dyadic data, types of research questions that APIM and reciprocal OWM models can help answer, and specific analytic techniques involved in testing dyadic hypotheses.