how are nasa engineers motivated?

162 Pages·2008·0.78 MB·English

by  Nicola Smith

HOW ARE NASA ENGINEERS MOTIVATED? AN ANALYSIS OF FACTORS THAT
INFLUENCE NASA GODDARD ENGINEERS’ LEVEL OF MOTIVATION

HOWARD ERIC KEA

A DISSERTATION

Submitted to the Ph.D. in Leadership & Change Program
of Antioch University
in partial fulfillment
of the requirements for the degree of
Doctor of Philosophy

July, 2008
This is to certify that the dissertation entitled:

HOW ARE NASA ENGINEERS MOTIVATED? AN ANALYSIS OF FACTORS THAT
INFLUENCE NASA GODDARD ENGINEERS’ LEVEL OF MOTIVATION

prepared by

Howard Eric Kea

is approved in partial fulfillment of the requirements for the degree of Doctor of Philosophy in
Leadership & Change.

Approved by:

Jon Wergin, Ph.D. Chair date

Elizabeth Holloway, Ph.D. Faculty Reader date

Carol Baron, Ph.D. Faculty Reader date

Charles Seashore, Ph.D. External Reader date
Copyright 2008 Howard E. Kea
All rights reserved
This work is dedicated to the memory of my father
Andrew Millard Kea, Capt. USAF
Who let nothing deter him from pursuing his life’s dream:
“To fly airplanes…”
Acknowledgments
There are many people I would like to thank for supporting me throughout this journey. I
had the gifts of listening ears, coaching, cheerleading, shoulders to cry on, and laughter from
family members, friends, fellow cohort members, and faculty. I am truly grateful to each of them
for encouraging and challenging me to dig deeper, and to slow down when I needed to.
Thank you to Dr. Laurien Alexandra, for conceiving and birthing this fabulous program,
and for inviting me on this journey and encouraging me along the way. Thank you to Dr.
Elizabeth Holloway, my advisor and committee member, for guiding me along the journey,
encouraging me along the way, and helping me to get clarity on my dissertation. Thank you to
Dr. Jon Wergin, my committee chair, for guiding me to a manageable dissertation topic and
allowing me to put it in my voice-- you also make a damn good martini as well! Thank you to
Dr. Carol Baron, committee member, ILA mentor, and my statistics instructor, for the many
hours on the phone and at your house in helping me to understand my data and introducing me to
the “art” of quantitative analysis. Thank you to Dr. Charles Seashore, external reader, for your
insightful feedback on my dissertation. Special thanks to Dr. Michael Broom, my coach and ILA
mentor, for stretching me well beyond what I thought possible which led me to finding my own
voice.
Thank you to Cohort 1: Scott, Karen, Mia, Beth, Bruce, Peggy, Miriam, and Bill, we
were the nine pioneers who stuck it out to the end. Thank you for the love, support, and life- long
friendship.
Thank you to my NASA family and particularly to Denise Davis, my boss, for advocating
on my behalf for the NASA Study Fellowship that enabled me to complete my dissertation and
to directors, Ron Brade and Orlando Figueroa for granting me permission to conduct my
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research at NASA Goddard. Thank you to all the engineers who participated in the study and
made this work possible.
Thank you to my mother for planting seeds when I was a child that education is the key
to success in life and to my sister, Dr. Karen Kea for her quiet inspiration. Thank you to my
children Chase and Mallory, for giving Dad time to study and for your bright smiles that bring
me joy each day. And finally, thank you to my wife Nikki, for sticking by my side through my
personal struggles. You are my best friend. This PhD program brought us together and without
your unconditional love and support I could not have completed this journey.
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Abstract
NASA is an organization known for pushing the envelope of engineering and scientific
achievement. It can be argued that engineers working for NASA are intrinsically highly
motivated due to the nature of the work and the mission of NASA. This study explores how
supervisor behaviors, both intrinsic and extrinsic and demographic factors influence motivation
of NASA Goddard engineers in their current environment. Recent Congressional and Office of
Management and Budget (OMB) policies, such as full cost accounting, levy strict oversight of
project spending. As a result of these policies, NASA engineers must now focus their attention
on getting assigned work on funded projects in addition to pursuing technical innovation and
creativity. The literature is replete with previous studies on motivation of engineers and
scientists. These studies investigated Maslow (1970), Vroom (1964), Herzberg (1971), and
Deci’s (1975) theories of motivation. Today, the workplace is much more diverse with regard to
race, gender, and age. A web-based survey was used to collect data from a sample of engineers at
NASA Goddard Space Flight Center. 260 out of 583 engineers responded to the survey. 238
cases provided useable data for analysis. A hierarchical regression analysis revealed the
demographic categories of females and non-whites did not significantly predict the level of
motivation of engineers. Age was a significant factor influencing motivation. The age group of
39 and under had less of an influence on motivation and the age group of 40 and over had more
of an influence. The over 60 age group had a very significant positive influence on motivation.
Other significant factors influencing motivation were: supervisor behaviors, intrinsic factors such
as feedback and competence, and extrinsic factors such as benefits, rewards and promotions. The
results support the argument that NASA engineers are motivated by getting feedback from their
immediate project supervisor, that they feel competent in their jobs, and that the benefits,
rewards, and promotions fairly reflect their contribution and loyalty to the mission of NASA.
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TABLE OF CONTENTS
Acknowledgments i
Table of Contents iv
Abstract iii
List of Tables vi
List of Figures vi

Chapter I: Introduction 1
Problem Statement 1
History and Culture of NASA 1
Purpose of and Justification for this Study 10
Personal Connection to the Study 11
Research Questions 13
Description of Terms--Matrixed Employees 14
Organization to be Studied 15
Summary of Chapters 17
What is Motivation? 19
Motivation in the Workplace 22
Leadership and Motivation 24
The Engineering Profession 30
Motivation of Engineers as a Professional Group 34
Supervisor Impacts on Engineer Motivation 39
Previous Empirical Studies on Engineer Motivation 47
Summary 58

Chapter III: Method 61
Design of the Study 62
Study Population and Sample 64
Reliability and Validity 65
Data Collection 66
Data Analysis 67
Summary 70

Chapter V: Results 74
Overall Response Rate 74
Descriptive Statistics 75
Reliability 76
Factor Analysis 77
Regression Analysis 84
Summary 88

Chapter VI: Discussion 90
Summary of the Study 90
Study Limitations 97
Implications for NASA Management 98
Further Study 99
Concluding Remarks 100
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Appendices 101
APPENDIX A--SURVEY INSTRUMENT 102
APPENDIX B--NASA LETTERS OF APPROVAL 110
APPENDIX C--IRB APPROVAL FORM 113
APPENDIX D--DATA SET 116
APPENDIX E--OPEN ENDED RESPONSES AND COMMENTS 117
APPENDIX F--DESCRIPTIVE STATISTICS 138

References 146

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List of Tables
Table 1.1 Demographic Breakdown of Total U.S. Federal Government Employed Engineers 3

Table 1.2 NASA 2007 Engineering Workforce 5

Table 1.3 GSFC 2007 Engineering Workforce 5

Table 2.1 Differences in Vocational Interests between Scientists and Engineers 33

Table 2.2 A Framework for Work Motivation 37

Table 3.1 Variables Predicting Motivation Levels of NASA Goddard Engineers 69

Table 5.1 Sample Size Compared to Response Rate and Weights 75

Table 5.2 Variables with Significant Kurtosis 76

Table 5.3 Reliability of Each Scale 76

Table 5.4 OCQ Scale Factor Analysis Variables 78

Table 5.5 Proj_Supr Scale Factor Variables 79

Table 5.6 Admin_Supr2 Scale Items 80

Table 5.7 JCI_Autonomy Scale Variables 80

Table 5.8 JCI_Feedback Scale Variables 81

Table 5.9 EWS_Competence Scale Items 81

Table 5.10 Pay and Promotion Scale Items 82

Table 5.11 Benefits and Rewards Scale 82

Table 5.12 Policy Scale 83

Table 5.13 Descriptive Statistics for New Variables 83

Table 5.14 Regression Analysis for Motivation Scale of 1 to 7 Using Weighted Data 86

Table 5.15 Regression Analysis for OCQ_Motivation using weighted Using Weighted Data 87

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