z-logo
open-access-imgOpen Access
Development of a Quality Decision-Making Scenario to Measure How Employees Handle Out-of-Condition Grain
Author(s) -
Gretchen A. Mosher,
Nir Keren,
Charles R. Hurburgh
Publication year - 2013
Publication title -
applied engineering in agriculture
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.276
H-Index - 54
eISSN - 1943-7838
pISSN - 0883-8542
DOI - 10.13031/aea.29.9795
Subject(s) - decision quality , work (physics) , quality (philosophy) , task (project management) , tracing , process (computing) , process tracing , operations management , business , measure (data warehouse) , marketing , process management , operations research , computer science , engineering , mechanical engineering , philosophy , systems engineering , epistemology , database , politics , law , political science , patient satisfaction , operating system
Quality management systems have been shown to improve inventory management, increase internal efficiencies, and enhance the ability of businesses to meet customer specifications, but little work has explored the role of employee decisions in the success of such systems. This work used the methodology of process-tracing to examine the decision-making process of grain elevator employees (n=164) as they determined how to handle out-of-condition corn. Employees overwhelmingly chose to either follow management orders or to make a "non-choice" rather than to make a decision which would preserve the quality of the grain. Employees equally emphasized decision-making dimensions of storage risk and company policy in their decision process, suggesting a conflict in how employees approach the quality decision task.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom