Year: 2004
Type: article
Abstract: Performance Tracking through the Work Compatibility Visual ToolObjective: This study proposes a decision-support framework to track the state of the human-at-work system on an operational basis.The work compatibility model provides a multi-dimensional diagnostic of the human-at-work system.By integrating the work compatibility model into a visual framework, management can make informative decisions that contribute to the improvement of human performance Background: Examples of multidimensional models can be found in performance measuring systems and human performance measures.Performance measuring systems, either hierarchical or balanced models, are focused on the reduction of operational variables to financial performance.Human performance measures rely on respondents to weigh different factors and define the best rules for aggregation.In the work compatibility model, respondents rate work-factors as energizers and demands on the system.An expert model uses a matrix function to quantify the degree of compatibility.Based on the matrix output, operating zones determine how far the system is from the optimum performance. Conceptual model:The matrix function of the expert solution is transformed into a plane with two regions set along the compatibility line.Work factors are aggregated into two vectors, one on each region of the plane, and the resultant of the two vectors provides two indexes: the yield ratio, a relative measure of the magnitude of vector, and the efficiency ratio, a relative measure of the angle between the two vectors.A Visual Basic application is developed to implement the proposed quantitative methods.The continuous model is tested with data from a manufacturing company to analyze the behavior of the response function.5.1 Response function 5.2 Visualization 5.3 Decision Process 5.4 Conclusions 5.
Author: O. Paez
Institution: University of Cincinnati
Language: English
Topic: Ergonomics and Human Factors
Subfield: Human Factors and Ergonomics
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2266160108