The day-of-invitation effect on participation in web-based studies.

Several methods have been proposed to promote participation in web-based research. Here, we examine a technique that is available at no cost: Inviting respondents per e-mail on a particular day of the week. We base our reasoning on such a day-of-invitation effect upon theories on variations in mood and work performance over the week. We conducted five experiments with large and heterogeneous samples to find out whether such effects apply for response rate (i.e., visiting the first page of a study) and retention rate (i.e., completing the study) in web-based studies. We found evidence of a small but significant day-of-invitation effect. Response rate is high at the beginning of the workweek and falls to a low on Friday. Exploratory analyses showed that this decline is higher for employed (vs. nonemployed) persons. Effects on retention rate appear to follow a less straightforward pattern. We discuss possible mechanisms that might account for the day-of-invitation effect and recommend inviting participants on Monday or Tuesday.

A Daily Diary Study on the Consequences of Networking on Employees' Career-Related Outcomes: The Mediating Role of Positive Affect.

Although researchers have shown that networking is positively associated with numerous long-term outcomes (e. g., salary, promotion) investigations of proximal outcomes of networking are still scarce. Building on Conservation of Resources theory (COR; Hobfoll, 2001, 2011) and conducting a daily diary study over five consecutive working days (N = 160 academics), we investigated short-term effects of networking on employees' career-related outcomes (i.e., career optimism and career satisfaction), job attitudes (i.e., job satisfaction), and well-being (i.e., emotional exhaustion). Further, we suggested that positive affect would act as a mediator. Results from hierarchical linear modeling (HLM) showed that daily networking relates to all four outcome variables. Moreover, positive affect mediated three of four hypothesized relationships, with a marginally significant effect for career satisfaction. By providing evidence for valuable short-term benefits of networking, our study extends existing research on positive long-term effects (for example on salary, promotions). Findings broaden the scope by integrating networking research with a positive organizational behavior perspective. We discuss practical implications with regard to career intervention strategies, study limitations, and prospects for future research.

Implicit Motives as Determinants of Networking Behaviors.

In today's world of work, networking behaviors are an important and viable strategy to enhance success in work and career domains. Concerning personality as an antecedent of networking behaviors, prior studies have exclusively relied on trait perspectives that focus on how people feel, think, and act. Adopting a motivational perspective on personality, we enlarge this focus and argue that beyond traits predominantly tapping social content, motives shed further light on instrumental aspects of networking - or why people network. We use McClelland's implicit motives framework of need for power (nPow), need for achievement (nAch), and need for affiliation (nAff) to examine instrumental determinants of networking. Using a facet theoretical approach to networking behaviors, we predict differential relations of these three motives with facets of (1) internal vs. external networking and (2) building, maintaining, and using contacts. We conducted an online study, in which we temporally separate measures (N = 539 employed individuals) to examine our hypotheses. Using multivariate latent regression, we show that nAch is related to networking in general. In line with theoretical differences between networking facets, we find that nAff is positively related to building contacts, whereas nPow is positively related to using internal contacts. In sum, this study shows that networking is not only driven by social factors (i.e., nAff), but instead the achievement motive is the most important driver of networking behaviors.

Effects of networking on career success: a longitudinal study.

Previous research has reported effects of networking, defined as building, maintaining, and using relationships, on career success. However, empirical studies have relied exclusively on concurrent or retrospective designs that rest upon strong assumptions about the causal direction of this relation and depict a static snapshot of the relation at a given point in time. This study provides a dynamic perspective on the effects of networking on career success and reports results of a longitudinal study. Networking was assessed with 6 subscales that resulted from combining measures of the facets of (a) internal versus external networking and (b) building versus maintaining versus using contacts. Objective (salary) and subjective (career satisfaction) measures of career success were obtained for 3 consecutive years. Multilevel analyses showed that networking is related to concurrent salary and that it is related to the growth rate of salary over time. Networking is also related to concurrent career satisfaction. As satisfaction remained stable over time, no effects of networking on the growth of career satisfaction were found. (PsycINFO Database Record (c) 2009 APA, all rights reserved).

Individual payments as a longer-term incentive in online panels.

Does it pay to pay online panel members? A three-wave longitudinal experiment was conducted with an online panel to examine whether per person payments, paid through an online intermediary, influence response and retention rates. In the payment condition, participants were promised payment for participation at each wave, whereas control participants were not offered any payment. The promise of a payment had a negative effect on response in Wave 1, but a positive effect on response in Wave 2. Payment had no significant effect on retention. Completing a given wave was an indicator for responding to a subsequent invitation.

Exploring item and higher order factor structure with the Schmid-Leiman solution: syntax codes for SPSS and SAS.

To ease the interpretation of higher order factor analysis, the direct relationships between variables and higher order factors may be calculated by the Schmid-Leiman solution (SLS; Schmid & Leiman, 1957). This simple transformation of higher order factor analysis orthogonalizes first-order and higher order factors and thereby allows the interpretation of the relative impact of factor levels on variables. The Schmid-Leiman solution may also be used to facilitate theorizing and scale development. The rationale for the procedure is presented, supplemented by syntax codes for SPSS and SAS, since the transformation is not part of most statistical programs. Syntax codes may also be downloaded from www.psychonomic.org/archive/.