In spite of the increasing demand for virtual cooperation, still relatively little is known about the knowledge, skills, abilities, and other characteristics (KSAOs) individuals need for virtual teamwork. Thus, the current paper aims at synthesizing the existing literature into a comprehensive model of virtual teamwork KSAOs. To this end, we review (a) existing frameworks of KSAO requirements for virtual teamwork, (b) challenges posed by different facets of virtuality, and (c) KSAOs particularly relevant for meeting the identified challenges. The results of this review are integrated into a holistic model of virtual teamwork KSAOs with distal characteristics (personality, experience) and more proximal qualities (knowledge, skills, and motivation). Research gaps as well as avenues for future research will be outlined and applications for virtual team staffing and training will be discussed.

The bifactor model is a widely applied model to analyze general and specific abilities. Extensions of bifactor models additionally include criterion variables. In such extended bifactor models, the general and specific factors can be correlated with criterion variables. Moreover, the influence of general and specific factors on criterion variables can be scrutinized in latent multiple regression models that are built on bifactor measurement models. This study employs an extended bifactor model to predict mathematics and English grades by three facets of intelligence (number series, verbal analogies, and unfolding). We show that, if the observed variables do not differ in their loadings, extended bifactor models are not identified and not applicable. Moreover, we reveal that standard errors of regression weights in extended bifactor models can be very large and, thus, lead to invalid conclusions. A formal proof of the nonidentification is presented. Subsequently, we suggest alternative approaches for predicting criterion variables by general and specific factors. In particular, we illustrate how (1) composite ability factors can be defined in extended first-order factor models and (2) how bifactor(S-1) models can be applied. The differences between first-order factor models and bifactor(S-1) models for predicting criterion variables are discussed in detail and illustrated with the empirical example.

Objective: The symmetry principle and the frame‐of‐reference perspective have each made contributions to improving the measurement of personality. Although each perspective is valuable in its own right, we argue that even greater improvement can be achieved through the combination of both. Therefore, the goal of the current article was to show the value of a combined lens‐model and frame‐of‐reference perspective.Method: We conducted a literature review to summarize relevant research findings that shed light on the interplay of both perspectives and developed an integrative model.Results: Based on the literature review and on theoretical grounds, we argue that a basic premise of the frame‐of‐reference literature––that personality items are open to interpretation and allow individuals to impose their own contextual framings––should be considered from a symmetry perspective. Unintended context‐specificity in items may “spread” to personality facets and domains, and thus, impact the symmetry of personality measures with other criteria. As the individuals´ frames‐of‐reference and (a)symmetric relationships are not always apparent, we term them as “hidden.”Conclusions: The proposed combination of lens‐model and frame‐of‐reference perspectives provides further insights into current issues in personality research and uncovers important avenues for future research.

A large body of research has examined the link between personality and face-to-face (FtF) communication knowledge, skills, abilities, and other characteristics (KSAOs). With the rise of digital media, text-based computer-mediated (CM) communication KSAOs have gained increasing attention. We conducted two studies to investigate how personality relates to KSAOs in the different contexts of FtFandCM communication. Contrasting perspectives hypothesize that the results in the FtF and CM contexts would be very similar or distinctly different. In Study 1 (n= 454), an online panel study, the Big Five personality dimensions were assessed and their relationships to FtF and CM communication KSAOs were investigated. Structural equation models and relative weight regression analyses showed that these personality dimensions, mostly extraversion and neuroticism, explained more variance in FtF as compared to CM communication KSAOs. Study 2 (n= 173), conducted in a laboratory context, showed similar results compared to Study 1. In addition, when the Big Five personality dimensions were assessed with a CM frame of reference, more variance was explained in CM than in FtF communication KSAOs. These results point to the importance of considering context effects in communication and in personality research: FtF and CM communication KSAOs need to be differentiated. If not properly contextualized, the relevance of personality and communication competencies in predicting criteria may be underestimated due to contextual mismatches.

Dispositional communication competencies can be assessed in (a) a generic form that does not include any reference to a particular medium of interaction or in (b) a communication medium-specific version. To date, little is known about the specific media that individuals use as a reference and the weights they assign to them when responding to generic communication items – an important research gap because the use of diverse communication media has risen considerably during the COVID-19 pandemic. Based on media theories, two hypotheses were derived: Generic ratings contain a “hidden” face-to-face (FtF) communication framing that is dominant in the cognitive processing (media naturalness perspective) versus media are equally weighted in the mental aggregate of respondents (adaptation perspective). According to a preregistered study plan, generic and medium-specific communication items were assessed to investigate these hypotheses (referencing FtF, videoconferencing, chat, and e-mail interaction contexts). Training (n = 200) and test (n = 389) datasets were analyzed using latent variable modeling. Results indicated that generic ratings have a strong hidden FtF framing. These hidden framings impact the predictive power of the competencies to explain communication criteria (i.e. communication satisfaction). Exploratory analyses indicated that individual differences in media experience may affect the framings.