Industrial Organizational Psychology

Rodger Griffeth's Research Lab



   Dr. Griffeth's research involves investigations of organizational turnover and human resource management.

   Test-Retest of the Employment Opportunity Index and Several Turnover Related Measures

   Griffeth and colleagues (2005) developed the Employment Opportunity Index (EOI), a multidimensional instrument to assess the of role of employee job market perceptions.  The current study examined the test-retest reliability of the EOI five dimensions with three different samples.  The results show some variation among the dimensions.

  Development and Validation of a Multidimensional Measure of the Turnover 
Events and Shocks Scale (Tess)

   Over three separate studies, we developed and validated an inventory of critical workplace events that might induce thoughts of quitting—or “shocks to the system.”  This construct plays a pivotal role in Lee and Mitchell’s (1994) unfolding model, being supposedly responsible for the nontraditional ways by which leavers vacate their job.  The unfolding model—and the centrality of shocks—have primarily been validated by retrospective reports by former leavers.  To better corroborate this model and shocks, we developed and validated a psychometrically valid measure that assesses 55 common workplace events and/or shocks.  In Study 1 (a large sample of nurses), factor analysis identified six distinct factors for workplace shocks.  Using survival analysis with scales based on these factors predicted turnover (beyond that accounted for by job attitudes and perceived alternatives).  Study 2 (with case workers) replicated this factor structure using confirmatory factor analysis and determined that weighting events by their “causal impact” only slightly improved predictive strength over unweighted predictors.  Study 3 (with retail store personnel) determined that shock scales predicted job longevity with survival analysis.



Jeff Vancouver's Research Lab


      Dr. Vancouver oversees two labs with overlapping interests. The Laboratory for the Study of Self-Regulation focuses on developing an integrative theory of human motivation and behavior. Specifically, the self-regulation perspective suggests that humans (and other organisms) seek to obtain and maintain goals (i.e., desired states) for themselves and their environments. Goal striving is represented as a simple negative feedback loop or control process (i.e., like the cruise control of car). The self-regulation perspective holds that many goals, and thus feedback loops, exist with humans. Understanding how individuals allocate resources among these goals is key to understanding human behavior. To some extent this likely involves representations of contingencies or beliefs about capacities (e.g., self-efficacy; outcome expectancies). Indeed, much of the work in the lab is devoted to the role of self-efficacy beliefs (or their lack of a role) in human behavior. Also, because the goal striving is dynamic, nonlinear, and complex (due to the large number of goals), Dr. Vancouver uses computational models to represent theories of how the processes operate. Toward that end, Dr. Vancouver directs another lab, called HEIDi (Human-Environment Interaction Dynamics initiative) that aligns scholars from other disciplines within Psychology, Engineering and Computer Science, Philosophy, and other areas. These scholars are also interested in representing human behavior computationally and in terms of the interactions between the person and his or her environment.    

 

Recent and important publications:

Overviews of the general areas of inquiry by Dr. Vancouver can be found in:

  •  Vancouver, J. B. (in press). Motivation. Chapter in the Handbook of Human-Systems Integration (Boehm-Davis, F. Durso, and Lee, Eds.). Washington, DC: APA
  • Vancouver, J. B., & Day, D. V. (2005). Industrial and Organization Research on Self‑Regulation: From Constructs to Applications. Applied Psychology: International Review, 54, 155-185. 
  • Austin, J. T., & Vancouver, J. B. (1996). Goal constructs in psychology: Structure, process, and content. Psychological Bulletin,120(3), 338-375.

An overview of Dr. Vancouver's the general theoretical approach can be found in:
  • Vancouver, J. B. (2008).  Integrating self-regulation theories of work motivation into a dynamic process theory. Human Resource Management Review, 18, 1-18.

 

Examples of computational models representing can be found in:

  •  Vancouver, J. B., Weinhardt, J.M., Vigo, R (in press). Change one can believe in: Adding learning to a computational model of self-regulation. Organizational Behavior and Human Decision Processing. 
  • Vancouver, J. B., Weinhardt, J. M., & Schmidt, A. M. (2010). A formal, computational theory of multiple-goal pursuit: Integrating goal-choice and goal-striving processes. Journal of Applied Psychology, 95, 985-1008.
  • Scherbaum, C. A., & Vancouver, J. B. (2010). If we produce discrepancies, then how? Testing a computational process model of positive goal revision. Journal of Applied Social Psychology40, 2201-2231.
  • Vancouver, J. B., Tamanini, K. B., & Yoder, R. J. (2010). Using dynamic computational models to reconnect theory and research: Socialization by the proactive newcomer example.Journal of Management, 36, 764-793. 
  • Vancouver, J. B. & Scherbaum, C. A. (2008). Do We Self-Regulate Actions or Perceptions? A Test of Two Computational Models. Computational and Mathematical Organizational Theory, 14, 1-22.
  • Vancouver J. B., Putka, D. J., & Scherbaum, C. A. (2005). Testing a Computational Model of the Goal‑Level Effect: An Example of a Neglected Methodology. Organizational Research Methods8, 100‑127.

 

Papers on how to create computational models and what might be good problems to model in the field are: 

  • Vancouver, J.B., & Weinhardt, J.M., (2012). Modeling the mind and the milieu: Computational modeling for micro-level organizational researchers. Organizational Research Methods, 15, 602-623.
  • Weinhardt, J. M. & Vancouver, J. B. (2012). Computational models and organizational psychology: Opportunities abound. Organizational Psychology Review, 2, 267-292.

 

Papers on Self-efficacy include:

  • Vancouver, J. B., Gullekson, N. L., Morse, B. J. & Warren, M. A. (in press). Finding a Between-Person Negative Effect of Self-Efficacy on Performance: Not Just a Within-Person Effect Anymore. Human Performance.
  • Vancouver, J.B., Weinhardt, J.M., Warren, M., Covey, A., Purl, J., Milakovic, A., & Li, X. (2013). Do management scholars mistakenly believe in the capacity of self-efficacy? In D. Svyantek & K. Mahoney (Eds.), Received Wisdom, Kernels of Truth, and Boundary Conditions in Organizational Studies (pp. 77-103). Charlotte, NC: Information Age Publishing.
  • Vancouver, J. B., More, K. M., & Yoder, R. J. (2008). Self‑efficacy and resource allocation: Support for a nonmonotonic, discontinuous model. Journal of Applied Psychology, 93, 35-47.
  • Vancouver, J. B. & Kendall, L. N. (2006). When self‑efficacy negatively relates to motivation and performance in a learning context. Journal of Applied Psychology91, 1146-1153.
  • Vancouver, J. B., Thompson, C. M., Tischner, E. C., & Putka, D. J. (2002). Two studies examining the negative effect of self-efficacy on performance. Journal of Applied Psychology,87, 506–516.
  • Vancouver, J. B., Thompson, C. M., & Williams, A. A. (2001). The changing signs in the relationships between self‑efficacy, personal goals and performance. Journal of Applied Psychology86, 605-620.

 

Responses to criticism of Dr. Vancouver's work are: 

  • Vancouver, J. B. (2012). Rhetorical Reckoning: A Response to Bandura. Journal of Management38, 465-474.
  • Vancouver, J. B. (2005). The Depth of History and Explanation as Benefit and Bane for Psychological Control Theories. Journal of Applied Psychology90, 38-52.

 



  
Industrial Organizational Psychology
Porter Hall 306
Athens, OH 45701

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