Date of Award
Spring 2014
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Engineering Management & Systems Engineering
Program/Concentration
Engineering Management
Committee Director
Pilar Pazos
Committee Member
Steven Cotter
Committee Member
Resit Unal
Call Number for Print
Special Collections LD4331.E555 M23 2014
Abstract
This study proposes a model to diagnose organizations using the mathematical principles of data envelopment analysis (DEA) to the variables generated using competing values framework (CVF) in order to evaluate overall organizational effectiveness. The notion of organizational effectiveness is abstract and difficult to measure due to its complexity and multi-functional nature. Over the years, measurement of organizational effectiveness has remained a challenge due to the lack of agreement on the factors that should be assessed to determine effectiveness. This research is aimed at shedding some light into this topic by using data envelopment analysis as a tool to measure relative efficiency based on a predefined effectiveness model. The effectiveness model is prepared on basis of competing values framework.
The relative efficiency scores that are obtained though this integrated approach compare and suggest the best practices that may be employed by an organization. In this research, a measurement model integrating CVF and DEA is developed and tested in context of power and hand tool manufacturers. The results obtained tested the feasibility of the model to assess organizational effectiveness. The findings may provide useful information to company stakeholders and business analysts about the factors that influence critical outcomes and compare that information with that of major competitors.
Rights
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DOI
10.25777/s9t6-mt72
Recommended Citation
Macherla, Raghavender.
"Assessing Organizational Effectiveness Through the Competing Values Framework A Data Envelopment Approach"
(2014). Master of Science (MS), Thesis, Engineering Management & Systems Engineering, Old Dominion University, DOI: 10.25777/s9t6-mt72
https://digitalcommons.odu.edu/emse_etds/228
Included in
Data Science Commons, Management Sciences and Quantitative Methods Commons, Operational Research Commons, Organizational Behavior and Theory Commons