In this article, the authors present a model linking immediate affective experiences to within-person performance. First, the authors define a time structure for performance (the performance episode) that is commensurate with the dynamic nature of affect. Next, the authors examine the core cognitive and regulatory processes that determine performance for 1 person during any particular episode. Third, the authors describe how various emotions and moods influence the intermediary performance processes, thereby affecting performance. In the final section of the article, the authors discuss limitations, future research directions, and practical implications for their episodic process model of affect and performance.

Previous meta-analytic examinations of group cohesion and performance have focused primarily on contextual factors. This study examined issues relevant to applied researchers by providing a more detailed analysis of the criterion domain. In addition, the authors reinvestigated the role of components of cohesion using more modern meta-analytic methods and in light of different types of performance criteria. The results of the authors' meta-analyses revealed stronger correlations between cohesion and performance when performance was defined as behavior (as opposed to outcome), when it was assessed with efficiency measures (as opposed to effectiveness measures), and as patterns of team workflow became more intensive. In addition, and in contrast to B. Mullen and C. Copper's (1994) meta-analysis, the 3 main components of cohesion were independently related to the various performance domains. Implications for organizations and future research on cohesion and performance are discussed.

A common practice in applications of structural equation modeling techniques is to create composite measures from individual items. The purpose of this article was to provide an empirical comparison of several composite formation methods on model fit. Data from 1, 177 public school teachers were used to test a model of union commitment in which alternative composite formation methods were used to specify the measurement components of the model. Bootstrapping procedures were used to generate data for two additional sample sizes. Results indicated that the use of composites, in general, resulted in improved overall model fit as compared to treating all items as individual indicators. Lambda values and explained criterion variance indicated that this improved model fit was due to the creation of strong measurement models. Implications of these results for researchers using composites are discussed.

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In the organizational sciences, scholars are increasingly using experience sampling methods (ESM) to answer questions tied to intraindividual, dynamic phenomenon. However, employing this method to answer organizational research questions comes with a number of complex—and often difficult—decisions surrounding: (1) how the implementation of ESM can advance or elucidate prior between-person theorizing at the within-person level of analysis, (2) how scholars should effectively and efficiently assess within-person constructs, and (3) analytic concerns regarding the proper modeling of interdependent assessments and trends while controlling for potentially confounding factors. The current paper addresses these challenges via a panel of seven researchers who are familiar not only with implementing this methodology but also related theoretical and analytic challenges in this domain. The current paper provides timely, actionable insights aimed toward addressing several complex issues that scholars often face when implementing ESM in their research.

The use of experience sampling methods (ESM) and related techniques has exploded in organizational research. The goals of this review are to provide a focused perspective on the state of the art in using ESM and set the stage for what ESM will look like in the years to come. First, I provide a conceptually based discussion of exactly what is and what is not ESM. Next, I discuss the more advantageous elements of ESM that have surfaced from the range of disciplines that enjoy its use (e.g., reduced memory and methods biases), followed by the inevitable challenges that have sometimes limited its utility (e.g., issues with repeated assessment, missing data, and internal validity). Finally, I discuss three innovations of ESM (e.g., trait assessment, expansion to higher levels of analysis, and connection to big data) that seem likely to ensure its continued and expanded influence as a common tool for examining not only within-person psychological processes at work, but higher levels of analysis as well.

Work recovery research has focused mainly on how after-work break activities help employees replenish their resources and reduce fatigue. Given that employees spend a considerable amount of time at work, understanding how they can replenish their resources during the workday is critical. Drawing on ego depletion (Muraven & Baumeister, 2000) and self-determination theory (Deci & Ryan, 1985), we employed multi-source experience sampling methods to test the effects of a critical boundary condition, employee lunch break autonomy, on the relation between lunch break activities and end-of-workday fatigue. Although specific energy-relevant activities had a main effect on end-of-workday fatigue, each of these was moderated by the degree of autonomous choice associated with the break. Specifically, for activities that supported the psychological needs of relatedness and competence (i.e., social and work activities, respectively), as lunch break autonomy increased, effects switched from increasing fatigue to reducing fatigue. To the extent that lunch break activities involved relaxation, however, lunch break autonomy was only important when levels of relaxation were low. We conclude that lunch break autonomy plays a complex and pivotal role in conferring the potential energetic benefits of lunch break activities. Contributions to theory and practice are discussed. 2008-0505.

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