Keywords

Company Success, Key Performance Measures, Manufacturing Enterprises, Employee Morale, Quality, Ergonomics and Safety

Abstract

Profit, ergonomics, safety, employee morale, quality, efficiency, and productivity are critical components that greatly impact company success within manufacturing organizations. Therefore, it is essential that a valid and reliable systematic approach that encompasses all of these factors be developed for use by top management in today's rapidly changing manufacturing environment. Organizational-level decisions made based upon a single goal or narrow perspective that only considers one of the aforementioned components, such as profit, while ignoring others, such as employee morale, have proven harmful to the long term viability and success of manufacturing companies. Often organizational leaders are not adequately equipped to consider multiple factors that are pertinent to company success due to the complexity associated with considering a large number of organizational variables and the lack of quantitative tools and techniques to assist in this process. Thus, valid, reliable and readily available tools, methods, and techniques for integrating into decision making multiple components of profit, ergonomics, safety, employee morale, quality, efficiency, and productivity are highly needed in today's complex manufacturing business environment. This research responds to the need to develop quantitative models by creating a company success index. This index was developed using an approach to analyze and evaluate multiple factors at the strategic, tactical, and operational levels of an organization that are essential to achieve company success in manufacturing enterprises. The resulting company success index model was validated using information on market share (Specificity = 0%, Sensitivity & Accuracy = 87.5%). Future research related to this topic area should include additional studies to expand upon model validation and verification techniques.

Notes

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Graduation Date

2008

Advisor

Crumpton-Young, Lesia

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Industrial Engineering and Management Systems

Degree Program

Industrial Engineering

Format

application/pdf

Identifier

CFE0002173

URL

http://purl.fcla.edu/fcla/etd/CFE0002173

Language

English

Release Date

April 2008

Length of Campus-only Access

None

Access Status

Doctoral Dissertation (Open Access)

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