Dynamic performance

Research output: Contributions to collected editions/worksChapterpeer-review

Authors

This chapter reviews research on dynamic job performance. It summarizes the empirical literature and presents conceptual and theoretical approaches of conceptualizing performance change and performance fluctuations over time. It addresses longer term performance changes, describes predictors (e.g., ability, personality) and outcomes of individual differences in these changes, and incorporates a life-span perspective. It discusses vicious and positive cycles in which performance and its outcomes reinforce one another. It presents a within-person approach that focuses on short-term performance variability within persons and describes action-related and selfregulation process models of dynamic performance. The chapter closes with a taxonomy of dynamic performance processes and a research agenda for the future.
Original languageEnglish
Title of host publicationThe Oxford Handbook of Organizational Psychology
EditorsSteve W. J. Kozlowski
Number of pages31
Volume1
Place of PublicationOxford
PublisherOxford University Press
Publication date18.09.2012
Pages548-578
ISBN (print)9780195342826
ISBN (electronic)9780199968824
DOIs
Publication statusPublished - 18.09.2012

Recently viewed

Publications

  1. Anisotropy and mechanical properties of dissimilar Al additive manufactured structures generated by multi-layer friction surfacing
  2. Do children with deficits in basic cognitive functions profit from mixed age primary schools?
  3. Mechanical properties and microstructures of nano SiC reinforced ZE10 composites prepared with ultrasonic vibration
  4. Multi-view hidden markov perceptrons
  5. Covert and overt automatic imitation are correlated
  6. Material flow analysis between dynamic modelling and life cycle assessment
  7. Modeling and simulation of the heterogenous material behavior in thermal-sprayed coatings
  8. Atomic Animals
  9. Fruit Detection and Yield Mass Estimation from a UAV Based RGB Dense Cloud for an Apple Orchard
  10. Assessment of cognitive load in multimedia learning with dual-task methodology
  11. FROM THE EDITORS ERRORS IN ORGANIZATIONS
  12. The end of certainties
  13. The role of learning strategies for performance in mathematics courses for engineers
  14. Clusteranalyse als Methode zur Strukturierung großer Datenmodelle
  15. Evaluating the (cost-)effectiveness of guided and unguided Internet-based self-help for problematic alcohol use in employees
  16. Geometric Properties on the Perfect Decoupling Disturbance Control in Manufacturing Systems
  17. Semi-Supervised Generative Models for Multi-Agent Trajectories
  18. HPLC and chemometrics-assisted UV-spectroscopy methods for the simultaneous determination of ambroxol and doxycycline in capsule.
  19. Changes in processing characteristics and microstructural evolution during friction extrusion of aluminum
  20. Tschick
  21. Implementing the Kyoto Protocol without Russia
  22. Homogenization for a non-local coupling model
  23. Developing robust field survey protocols in landscape ecology
  24. Can guided introspection help avoid rationalization of meat consumption?
  25. Participation in multi-level policy implementation: exploring the influence of governance culture
  26. Microstructure and mechanical properties of Mg-3Sn-1Ca reinforced with AlN nano-particles
  27. Dynamic Semantic Web Content for Museum Guides
  28. Decision-making models for Robotic Warehouse
  29. Culture as an Engine of Local Development Processes
  30. Using (Quantitative) Structure-Activity Relationships in Pharmaceutical Risk Assessment
  31. Key criteria for developing ecosystem service indicators to inform decision making
  32. Going beyond certificates
  33. System versus Intention
  34. One step forward, two steps back
  35. Techno-economic assessment of non-sterile batch and continuous production of lactic acid from food waste
  36. Analysis of Dynamic Response of a Two Degrees of Freedom (2-DOF) Ball Bearing Nonlinear Model
  37. Practical Formalist
  38. Co-EM Support Vector learning
  39. Estimation of minimal data sets sizes for machine learning predictions in digital mental health interventions