m odeling the m ind and the m ilieu : computational modeling for organizational psychologists

18
MODELING THE MIND AND THE MILIEU: Computational Modeling for Organizational Psychologists

Upload: anne-cole

Post on 24-Dec-2015

219 views

Category:

Documents


2 download

TRANSCRIPT

MODELING THE MIND AND THE MILIEU:Computational Modeling for Organizational Psychologists

"MATHEMATICS IS THE LANGUAGE WITH WHICH GOD HAS WRITTEN THE UNIVERSE."   --  GALILEO GALILEI

Mathematics has not tended to be the language of theories in psychology and organizational science Math models need to be solved, but often seen as

intractable when describing human or organization behavior Computational models do not need to be solved

Computational models are algorithmic descriptions of process details, typically operationalized as computer programs that are dynamic and can be simulated (Taber & Timpone, 1996) JAP has only published one computational model, ever

(Vancouver, Weinhardt, & Schmidt, 2010) 0.3% of AMJ articles are computational models in last 11 years, only 1.3% of AMR articles included

computational models (nearly all macro or meso)

YET, COMPUTATIONAL MODELS:

Increase precision and transparency Less ambiguity of concepts and explanations Specific predictions (compared to natural

language theories) Assure internal (logical) consistency

Model works Accounts for phenomena claimed

Identify unanticipated consequences Simulations can lead to new findings

DYNAMICALLY CHALLENGED

Human ability to predict values in dynamic variables is low (even among those in STEM fields) Dynamic variables are variables with memory

Stocks, levels

Predicting the behavior of dynamic, nonlinear processes, interacting subsystems Forget about it

HINTZMAN (1990)

“To have one's hunches about how a simple combination of processes will behave repeatedly dashed by one's own computer program is a humbling experience that no experimental psychologist should miss” (p. 111).

OBJECTIVES: BY THE END OF THIS WORKSHOP YOU WILL KNOW HOW TO …

Identify a problem worthy of modeling Define the system to be modeled Build a model Evaluate a model

STEP 1: IDENTIFY PROBLEM

Dynamic phenomena All phenomena?

Existing theory Lot’s of talk, no models

Existing computational architectures Neural networks Systems dynamics Cybernetics

JOB ATTITUDES AND STRESS

Cybernetic, natural language theories on both topics

Hulin & Judge’s (2003) review of job attitude models

THE UBIQUITOUS COMPARATOR

STEP 2: SYSTEM DEFINITION

Unit(s) of analysis Individual in context

Problem boundary: just enough Core dynamic processes

Restrictions Time frame (100 days)

Variables: add as needed

 

 

 

 

 Well-Being

 Importance

  Coping

Physical and SocialEnvironment

Perception

Desires

Discrepancy

PART OF EDWARD’S THEORY OF STRESS AND WELL-BEING

STEP 3: BUILDING THE MODEL

Vensim System Dynamics platform (Forrester) Units often organizations or other larger systems Coopting for psychological modeling

Individual cognitive processes Individual in context

Open software Model setting: Unit of time; “Days”

Menu Sketch Tools

Main Toolbar

Output File Window

Simulation

Analysis Tools

Build Window (Where you build your model)

Lock Move Variable Level Variable

Arrow Rate Shadow Variable

InputOutput

Comment Delete Equation

Reference

SKETCH TOOLS

KEY VARIABLES IN THE MODEL

Variable NameType of Variable Time

Person/ Environment

perceptions Endogenous Time-varying Person

Environmental States Endogenous Time-varying* Environment

actions/coping behavior Endogenous Time-varying Person

discrepancies Endogenous Time-varying Person

desires Exogenous Constant (0) Person

Well-Being/Job Satisfaction Endogenous Time-varying* Person

importance Exogenous Constant (1) Person

TYPES OF DESIRES

Optima: Not too much; not to little Minima: Only values exceeding desire a

problem (e.g., budget) Maxima

Hard maxima: values exceeding desire ignored Soft maxima: more is better, but with

diminishing returns

STEP 4: EVALUATING THE MODELSimulations that worksPostdictionAssess assessment strategies

Will past designs and analysis have been diagnostic?

Hypothesis generation and testingStrong inference via model

comparisonDiffering predictionsModel fitting

Complexity (# parameters) vs. fit

DON’T MARRY YOUR MODEL!

Questions?

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.

Symposium: Understanding Dynamics Conceptually, Analytically, Computationally, and Empirically. Tuesday, Aug 7 201211:30AM - 1:00PM. Boston Park Plaza, Beacon Hill Room.

Web site: https://sites.google.com/site/motivationmodeling/home

Help from: Justin Weinhardt; Mike Warren; Amanda Covey; Justin Purl; Xiaofei Li