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What We Learned from a Computational Model of Job Attitudes and Stress. Justin M. Weinhardt & Jeffrey B. Vancouver a Ohio University. a This work is supported by NSF (grant #0851764), with funding from the American Recovery and Reinvestment Act of 2009. The Humble Scientist.

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what we learned from a computational model of job attitudes and stress

What We Learned from a Computational Model of Job Attitudes and Stress

Justin M. Weinhardt

&

Jeffrey B. Vancouvera

Ohio University

a This work is supported by NSF (grant #0851764), with funding from the American Recovery and Reinvestment Act of 2009.

the humble scientist
The Humble Scientist
  • Dynamics are difficult
  • Humans are ill-equipped
  • Support mechanisms have been created
    • mathematics
    • statistical analysis
    • computational modeling
the computational approach
The Computational Approach
  • Increases precision and transparency
  • Assures internal (logical) consistency
  • Identifies unanticipated consequences
  • Motivated a workshop:
    • Used attitudes/stress models as example
the ubiquitous comparator
The Ubiquitous Comparator
  • Hulin & Judge’s (2003) review of job attitude models
slide5

Part of Edward’s Theory of Stress and Well-Being

Desires

Discrepancy

Well-Being

Coping

Perception

Physical and Social

Environment

computational model vensim
Computational Model: Vensim

0

desires

Well-Being/

∫(-discrepancies)dt

discrepancies

discrepancies

desires - perceptions

Job Satisfaction

perceptions

actions/coping

actions/coping

Environmental States

perceptions

behaviors

behaviors

initial state

Environmental

∫("actions/coping behaviors" * environmental responsiveness)dt

0.1

States

environmental

responsiveness

problem 1 acting to make things worse
Problem #1: Acting to make things worse

desires

0

Well-Being/

discrepancies

Job Satisfaction

actions/coping

negative actions

perceptions

behaviors

initial states

|discrepancies|; or

discrepancies2 ; or

If d > 0, discrepancies

else, -discrepancies/2

1

Environmental

States

environmental

responsiveness

0.1

problem 2 runaway positive feedback loop
Problem #2: Runaway positive feedback loop

desires

0

Well-Being/

discrepancies

Job Satisfaction

actions/coping

perceptions

behaviors

initial states

1

Environmental

States

environmental

responsiveness

0.1

theoretical implications
Theoretical Implications

Here lies

affect as

mediator

theories

(e.g., social

cognitive

theory)

Here lies

symmetric

comparator

control

theories

actions/coping

If d > 0, discrepancies + 1

else, ediscrepancies

Equity

theory

(Adams,

1963)

behaviors

add opponent process
Add Opponent Process

equilibrium level

opponent

desires

process rate

Well-Being/

discrepancies

Job Satisfaction

actions/coping

perceptions

behaviors

Environmental

States

environmental

responsiveness

initial state

adding content theoretical richness of attitude models
Adding Content & Theoretical Richness of Attitude Models

felt deserved

respect

discrepancy 2

desired

respect

Well-Being/

discrepancy

Job Satisfaction

bias

perceived

actions/coping

perception

importance

respect

behaviors

of effort

Respect must be

submitted

earned

papers

accepted

papers

Respect given

reviewers

colleagues

initial state

responsiveness

responsiveness

theoretical richness of attitude models
Theoretical Richness of Attitude Models

felt deserved

respect

discrepancy 2

desired

respect

discrepancy

Well-Being/

discrepancy

3

Job Satisfaction

bias

perceived

actions/coping

perception

importance

perception of

respect

behaviors

of effort

effort of others

Respect must be

submitted

earned

papers

accepted

effort/achievement

papers

Respect given

of others

reviewers

colleagues

initial state

responsiveness

responsiveness

conclusion

https://sites.google.com/site/motivationmodeling/modeling-job-attitudeshttps://sites.google.com/site/motivationmodeling/modeling-job-attitudes

Conclusion
  • Translating theoretical notions into reasonable dynamic models will…
    • take some time (no pun intended)
    • require confronting assumptions
    • possibly lead to the elimination or integration of theories
    • lead to new insights
    • lead to predictions of trajectories and relationships not previously examined
    • Thank you!
further information
Further information
  • ORM tutorial: Vancouver, J.B., & Weinhardt, J.M., (online). Modeling the mind and the milieu: Computational modeling for micro-level organizational researchers. Organizational Research Methods.
  • Modeling in Org Psych: Weinhardt, J. M. & Vancouver, J. B. (in press). Is there a computational model in your future? Only the math will tell. Organizational Psychology Review.
  • Web site: https://sites.google.com/site/motivationmodeling/home