1. FACTORS CONTRIBUTING TO JOB
DISSATISFACTION AND ATTRITION
IN THE FEDERAL WORKPLACE
DENISE LOFTON,
DOCTORAL LEARNER
Feb. 7, 2012 Oral Defense Presentation

2. Presented in Partial Fulfillment of the Requirements for the
Degree
Doctor of Management in Organizational Leadership
Dr. Alex Lazo, Dr. Betty Ahmed,
Chair Member
The
Committee
University of
Phoenix
Dr. Gerald Nebeker, Denise Lofton,
Member Learner

3. ABSTRACT
The purpose of the quantitative correlational study was
to examine the relative influence of individual
demographics (gender, age, tenure, supervisory status,
location, and intent to leave) on job dissatisfaction (DV)
with facets of employment (leadership and knowledge
management, result orientation and performance, talent
management, and job dissatisfaction index) in the
Internal Revenue Service, and the Social Security
Administration (n = 2,203).

4. The Study Goals…
The study used demographic profiling to look beyond the
typical effect of independent variables on dependent
variables, to create a picture of groups and organizations
by like categories, and characteristics.
The study‟s outcome is significant to leadership as it
confirms the role of demographics in understanding the
factors contributing to job dissatisfaction.

5. BACKGROUND
Congress mandates that all Employees provide their
federal agencies assess perceptions in two important
employee perspectives and workplace categories: (1.)
develop improvement plans to leadership and management
address key findings. practices that contribute to
The bi-annual survey conducted agency performance, and (2.)
by the Office of Personnel employee satisfaction with
Management is the primary tool aspects of employment (OPM,
for data collection. 2008).

6. Problem Statement
The general problem is The specific problem is federal
agencies lack the knowledge
dissatisfied employees withdraw, needed to:
become disengaged, perceive  link job dissatisfaction to
attrition
employment to be less than
 adequately predict causation
desirable, and make the choice
 reduce loss of talent
to leave (Bowling, Beehr &
Lepisto, 2006; Ingersoll & Perda, OPM predicts the federal civilian
2006; Walker, 2007). workforce will see 60 percent
retirement eligibility by 2012 (OPM,
2009).

7. Purpose Statement
The purpose of the study was to The study looked at the change in
dissatisfaction among employee
investigate the relationship groups, by demographic
between job dissatisfaction with characteristics:
various facets of employment  Age,
 Gender,
and individual demographic
 Tenure,
characteristics for respondents
 Supervisory Status,
in the Federal Human Capital
 Location, and
Survey in 2006 and 2008, in two
 Intent to Leave
Executive Agencies.

8. Research Questions & Hypotheses
RQ1: What are the relative influences of the
respondent demographic characteristics (age, tenure,
gender, supervisory status, location, intent to leave),
on respondent dissatisfaction with facets of
employment (leadership & knowledge management,
results orientation & performance, talent
management, and job satisfaction index)?

9. Research Questions & Hypotheses
H1o: The respondent demographic characteristics do not
influence respondent dissatisfaction with facets of
employment
H1a: Tenure and location of the respondent exert the greatest
influence on dissatisfaction with facets of employment
(leadership & knowledge management, results orientation &
performance, talent management, job satisfaction index)

10. Research Questions & Hypotheses
RQ2: What are the differences in the influence of
respondent demographic characteristics on
dissatisfaction with facets of employment, between
SSA and IRS agencies?

11. Research Questions & Hypotheses
H2o: For the IRS and SSA, there are no differences in the
influences of respondent demographic characteristics on
dissatisfaction with facets of employment
H2a: For the IRS and SSA, there are differences in the
influences of respondent demographic characteristics on
dissatisfaction with facets of employment

12. Research Questions & Hypotheses
RQ3: What are the differences in the influences of
respondent demographic characteristics on
dissatisfaction with facets of employment between
2006 and 2008?

13. Research Questions & Hypotheses
H3o: For 2006 and 2008, there are no differences in the
influences of respondent demographic characteristics on
dissatisfaction with facets of employment.
H3a: For 2006 and 2008, there are differences in the influences
of respondent demographic characteristics on dissatisfaction
with facets of employment

14. Study Assumptions
 Study utilizes secondary analysis of existing data set and
as such re-purposes data
 Original respondents are examined solely by responses
and demographic characteristics (age, tenure, gender,
supervisory status, location, intent to leave)
 The truthfulness of the responses is assumed reliable
due to the privacy proffered and long-term acceptance of
the survey in the federal community

15. Study Scope
 Study utilizes data set derived from Office of Personnel
Management (OPM) Federal Human Capital Survey in the years
2006 and 2008
 Data used for the comparisons and analysis is limited to
respondents from two Presidential Management Council member
agencies, namely, the Internal Revenue Service, and the Social
Security Administration.
 The study organizations are representative of federal workforce
large agencies, have similar missions, workforce composition,
organizational structure, gender representation, customer base,
and stakeholder alliances (BPTW, 2010).

16. Study Limitations
 Each participating agency sample is based on employee
population at the time of the original survey, without regard to
gender, age, or tenure.
 The study utilized the quantitative responses to the 206 and
2008 federal workforce survey without any subsequent
qualitative aspects due to participant anonymity.
 The unique demographics of each agency extends the
possibility that an agency has an overrepresentation of males,
versus females, or young versus older workers, in the study
population

17. Literature Review
“There is a logical relation between our perceptual judgments of what is
real (in the naïve-realist sense) and our perceptual judgment about our own
experiences” (Murphey, 1994, p. 51).
The utility of job satisfaction measures seeks perception from a „real-world‟
point of view and gives as much consideration to the consequences of job
dissatisfaction, as to the causes (Seashore & Tabor, 1975).

18. Key Literary Findings
 Federal agencies and  Consideration of variables that
their respective leaders may influence employee
seek to understand perceptions, like age, gender,
better the causes of and tenure, requires
employee investigators to reevaluate
disengagement and past assumptions about
consider the trend an
workers as a cohort, and
important leader
challenge (Harter & account for differences in
Wagner, 2010) employee traits (Dychtwald,
Erickson, & Morrison, 2006).

19. Key Literary Findings
 Job dissatisfaction also  When aspects of employment
affects worker attitude, once considered important to
and the choice to remain the decision to join an
or leave employment, organization are no longer
even when the job or present, workers assess job
benefits may differ search capabilities, and
significantly (Berry, 2010; consider other options for
MSPB, 2008; Starks, employment where they may
2007). exist (Dooley, 2007; Judge &
Klinger, 2008).

20. Research Methodology
The study utilizes a quantitative Given the goals of the study, the
method with correlational design: large population, and multiple
independent variables, the
 Useful in determining predictors quantitative, correlational design,
using hierarchical regression
 Appropriate to test research questions
and study hypotheses techniques was appropriate and fit
for a reexamination of the Federal
 Allows researchers to identify and Human Capital Survey in 2006 and
isolate behaviors within and between
study variables 2008.
(Bryman, 2001; Creswell & Clark, 2007;
Trochim and Donnelly, 2008)

21. Research Methodology
The study utilizes secondary analysis
to re-purpose the original OPM survey: The inability to identity original
respondents and the lack of
 Reduces research time and cost access to original respondents
 Supports use of large data sets with supports use of a quantitative
proven reliability methodology and secondary
 Provides a unique opportunity to data analysis (Gelman & Hill,
continue study of specific phenomenon, 2007).
expand on prior knowledge, and „see‟
the world differently
(Bedeian, Ferris, & Kacmar, 1992;Neuman
2003; Thomas & Heck, 2001)

22. Study Population
Overview of Study Population and Sample Frame
Study population
consists of all Study Agency/ Year Original Sample Size
Respondent
respondents who Population
answered each IRS 2006 1,147 1,147
survey question in SSA 2006 1,317 1,317
the High Impact IRS 2008 1,153 1,153
Index and each
SSA 2008 5,959* 1,140a
demographic item
included in the a modified sample size calculation to equalize sample groups
study

23. Study Population
Sample Population (By Year, and Agency)
2006 2008
SSA IRS SSA IRS
650 484 690 411
Study
population was
comprised of: • 741 males
• 1,431 females
• Average age 50 – 59 (both agencies, both years)
• 1,407 supervisors
• 828 non-supervisors
• Average tenure over 20 years (both agencies)

24. High Impact Index
High-Impact Item Index, 2006, 2008
The High Impact Category Item # 2006 Item # 2008
Item Index
questions Leadership & Knowledge Mgmt Q9, Q17, Q36, Q55, Q57 Q9, Q17, Q37, Q56, Q58
comprised the
dataset extracted Results Orientation & Performance Q24, Q57 Q24, Q57
from the original
Office of
Talent Management Q2, Q18, Q59 Q2, Q18, Q60
Personnel survey
archive and re- Job Satisfaction Index Q5, Q6, Q54, Q58, Q61 Q5, Q6, Q55, Q59, Q62
purposed for use
Note: High-Impact Item Index for 2006 and 2008 includes the same questions, but the numbers
in this study changed due to a new survey item in 2008
There were a total of (17) survey questions examined by demographic
characteristic in the study. See Appendix C. for survey questions.

25. DATA COLLECTION
The survey questions were
grouped into four facets of
Five questions covering all employment:
facets comprise the new  Leadership and Knowledge
index: Management
Q5, Q6, Q54, Q58, Q61*  Results Orientation and
* Renumbered as Q. 62 in 2008 Performance
 Talent Management
 Job Dissatisfaction Index

26. DATA COLLECTION
Each response was coded to
allow for quantitative analysis
and results interpretation:
Response Scale
Responses coded as  The scale was appropriate to
1 = Dissatisfied each question asked, for
2 = Very Dissatisfied
0 = Neither, Satisfied, Very example…
Satisfied Q55 – How satisfied are you
with your involvement in
decisions that affect your
work?

27. DATA COLLECTION
Each demographic characteristic
was coded to allow for quantitative
analysis and results interpretation:
Response Scale  The scale was appropriate to
Each response option to the each question asked, for
Demographic characteristics example…
were grouped to facilitate X3: Tenure (in the agency, IRS, and
interpretation of results SSA) [under 1 year = 1; 1 to 5
years = 2; 6 to 10 years = 3; 11 to
20 years = 4; over 20 years = 5]
X6: Intent to Leave was coded:
No = 1; Yes, = 2.

28. DATA ANALYSIS
In the study, all categorical responses were
coded in numeric format to facilitate
regression and interpretation of results. Where
a, b, c, d, e, f, are coefficients, the regression
equation is:
Analysis Framework
The Y = a +bx1 + cx2+ dx3+ ex4+ fx5 + fx6 (1)
Data was examined by Research
Question, Hypotheses, In Equation 1,
Employment Facet and related x1 = age of the respondent,
demographic characteristic , using
hierarchical regression analysis x2 = gender of the respondent,
x3 = tenure (in the agency, IRS, and SSA),
x4: = supervisory status,
x5 = organization,
x6 = intent to leave.

29. DATA ANALYSIS – STEPWISE PROCESS
The change in R2 was determined
to see if there was a significant
change when a new variable is
added to the model. If the change
Regression Analysis
in R2 was significant (indicating
Step 1 – Gender & Age contribution to the model) the
Step 2 – Tenure
Step 3 – Supervisory Status and variable was retained in the next
Location step.
Step 4 – Intent to Leave
 The steps were repeated for
each research question, to test
hypotheses
See Appendix E for regression results for each facet of employment

30. DATA ANALYSIS – STEPWISE PROCESS
The change in R2 was determined
to see if there was a significant
change when a new variable is
Regression Analysis added to the model. If the change
The hierarchical regression in R2 was significant (indicating
analysis resulted in a total of (16) contribution to the model) the
models:
- 4 facets of employment variable was retained in the next
- 2 study agencies step.
- 2 study years
 The steps were repeated for
each research question, to test
hypotheses
See Appendix E for regression results for each facet of employment

31. DATA ANALYSIS – DESCRIPTIVE STATISTICS
Descriptive Statistics was used to :
 Examine the significant variable for each
facet of employment. For example:
Descriptives Variable Levels with Highest Dissatisfaction Score for the Significant Variables
The variable(s) with highest Demographic characteristic M SD n
level of dissatisfaction, by Tenure 11-20 years 1.74 2.14 329
significant variable, was
Non- Supervisor 1.70 2.25 813
determined for each facet of
employment Location – Field 1.48 2.05 1778
Intent to leave 2.24 2.55 470
Note: Results are for the Leadership and Knowledge Management facet of employment.
See Appendix F for descriptive statistics for all demographic variables, by facet of employment

32. Data Outcomes – RQ 1
Relative influence of IV, Full Sample
The coefficients for  Leadership and Knowledge Management
each demographic  The coefficient for tenure was positive and
characteristic was significant [ Beta .238, p < .01]
determined to  The coefficients for supervisor [ Beta -.525, p <
assess the .01 and location [ Beta -.320, p < .01] was
direction of the negative and significant
influence and the
 The coefficient for intent to leave was positive
significance.
and significant [ Beta 1.071, p < .01]

33. Key Study Findings
RQ 1
 Employees indicating work in a
 As tenure increased,
respondent Field location expressed more
dissatisfaction with dissatisfaction with facets of
facets of employment employment than did
increased Headquarters employees
 Non-supervisors
expressed more  Employees expressing an
dissatisfaction with intent to leave was more
facets of employment dissatisfied than those
than supervisors intending to remain

34. Data Outcomes – RQ 2
Relative Difference in influence of IV, Between IRS and SSA
The coefficients for  Leadership and Knowledge Management
each demographic  Tenure was significant for SSA only. The coefficient for
characteristic was tenure was positive and significant [ Beta .244, p < .01]
determined to  Supervisory status was significant for both agencies. The
assess the coefficients for supervisor IRS [ Beta -.484, p < .01] and
direction of the SSA [ Beta -.523, p < .01] were negative and significant
influence and the  Location was significant for IRS only. The coefficient for
significance. location was negative [ Beta -.002, p < .01 ]
 The coefficient for intent to leave was positive and
significant for both agencies: IRS [ Beta 1.123, p < .01],
SSA [ Beta 1.104, p < .01]

35. Key Study Findings
RQ 2
 Tenure continued to influence
 Location was significant, and employee dissatisfaction with facets,
negative for IRS only, in all when examined by Agency:
facets of employment  SSA employees expressed more
 Field employees expressed dissatisfaction as tenure
more dissatisfaction with facets
increased
of employment than
Headquarters  IRS employees expressed less
dissatisfaction as tenure
increased

36. Key Study Findings
RQ 2
 Intent to Leave was significant,  Supervisory status was significant for
and negative for both agencies, SSA only.
in all facets of employment  Non-supervisors expressed more
 Employees expressing an intent to dissatisfaction with facets of
leave demonstrated more employment than did supervisors
dissatisfaction with facets of
employment  The Job Dissatisfaction Index facet
of employment was affected by
NOTE: Future research is needed to employees dissatisfaction for:
determine if, and how often, the intent  Tenure (SSA =more years of service,
to leave was acted upon, and the more dissatisfaction; IRS more years of
related demographics service, less dissatisfaction

37. Data Outcomes – RQ 3
Relative Difference in influence of IV, for 2006 and 2008
The coefficients for  Leadership and Knowledge Management
each demographic  Tenure was significant for both years. The coefficient for
characteristic was tenure was positive 2006, [ Beta .265, p < .01]; 2008 [ Beta
.243, p < .01]
determined to
assess the  Supervisory status was significant for both agencies. The
direction of the coefficients for supervisor IRS [ Beta -.484, p < .01] and
SSA [ Beta -.523, p < .01] were negative and significant
influence and the
significance.  Location was significant for IRS only. The coefficient for
location was negative [ Beta -.002, p < .01]
 The coefficient for intent to leave was positive and
significant for both agencies: IRS [ Beta 1.123, p < .01],
SSA [ Beta 1.104, p < .01]

38. Key Study Findings
RQ 3
 Location was significant in  Tenure continued to influence
each facet of employment, but employee dissatisfaction with
not in the same years: facets, when examined by Year:
 Leadership and Knowledge  As SSA and IRS employees
Management in 2008 only.
tenure increased, the
 Results Orientation and expressed dissatisfaction
Performance, 2006 and 2008
with leadership and
 Talent Management and Job
knowledge management
Dissatisfaction Index in 2006
only increased

39. Key Study Findings
RQ 3
 Intent to Leave was significant,  Supervisory status was significant in
and negative for both years, in each facet of employment, but not in
all facets of employment each year:
 Employees expressing an intent  Leadership and Knowledge
to leave demonstrated more
dissatisfaction with facets of Management in 2006 only.
employment  Results Orientation and Performance,
Talent Management and Job
NOTE: Future research is needed Dissatisfaction Index in 2006 and 2008
to determine if, and how often, the
intent to leave was acted upon, and
the related demographics ( significance at p< .01 level )

40. Significance of Study Findings
The present study addresses the factors
that may contribute to job dissatisfaction The purpose of the research study was
and intent to leave in the federal to examine the relative influence of
workplace. demographic characteristics on
respondent dissatisfaction with facets of
 The range of available responses was employment, in the 2006 and 2008
provided, instead of collapsing them by Federal Human Capital Survey, for the
group, which allows the findings to be Internal Revenue Service and the Social
more specific and informative Security Administration.
 Findings support previous research
indicating age, in the presence of gender,
is insignificant as a predictor of
dissatisfaction (Cetin, 2006; Kacmar & Ferris, 1989)

41. Significance of Study Findings
The role of the supervisor and how well
supervisory performance is perceived
influences employee perception of The Judge study (2001) found a
dissatisfaction (Judge, Thoresen, Bono, & relationship between organizational
Patton, 2001) placement, individual performance, and
perceptions of supervisor performance
 The present study indicates supervisory status as (employee ratings, communications,
a negative and significant demographic policy, and practices).
characteristic in the study agencies and study
years
 Employees in non-supervisory (authoritative
positions) express more dissatisfaction in every
facet of employment
Note: Judge et al study included 312 research
samples, and over 54,000 respondents

42. Overview of Study Recommendations
 The federal workplace is a  The level of significance of employee
unique employer, with surveys increases when combined
many internal and external with specific information related to
stakeholders. With a experiences and individual
projected 60% attrition, via achievement in the organization
voluntary and normal (Joshi, 2010).
retirement, engaging the
workforce and increasing
productivity is key to
mission accomplishment Several recommendations are formed,
(Berry, 2011) ) based on study analysis and results.

43. Study Recommendations
Recommendations for leadership
consideration are offered for each
demographic characteristic Chapter 5 provides specific
included in the study: recommendations and supporting
theoretical framework for each
 Gender demographic characteristic addressed.
 Age
 Tenure
 Supervisory Status
 Location
 Intent to Leave

44. Study Recommendations
While age and gender, when
present together, were not New studies indicate females more
found significant in the study, likely to act on thoughts of leaving when
dissatisfied with career advancement,
the presence of over 1000 particularly when they believe that the
organization does not offer a chance to
females in the population apply a broader set of skills (Cech,
warrant future examination of Rubineau, Silbey, & Seron, 2011)..
employee perception, by
gender.

45. Study Recommendations
High unemployment generally means the
marketplace is flooded with talent,
though alignment between what is
required and what is available may mean Studies examining the role of
the number of unemployed will continue tenure in job dissatisfaction
to rise (BLS, 2011). reflect greater significance in the
presence of age (Kalleberg &
Loscocco, 1983).
 Agencies may consider stratifying
responses to annual surveys by age and
tenure, and compare the results to efforts
to recruit and retain high performing
individual to assess the gap.

46. Study Recommendations
Location of employee influenced
employee dissatisfaction with
facets of employment, for both Making critical decisions based
study agencies. on location may create new
silos and support negative
competition for scarce
 Leaders should consider re- resources (Rieger, 2011).
examine policies established
based on location, to ensure that
when taken as a whole they still
support goals of the organization.

47. Study Recommendations
Intent to Leave was a significant The reasons people leave jobs,
demographic characteristic in the
study agencies for each study year. careers, organizations, and
industries vary with age and
tenure, and often reflect the
relationship and interactions with
 The findings for the influence of intent managers and supervisors
to leave in each facet of employee (DeConinck & Johnson, 2009;
supports further investigation to
ascertain how long the employee Robinson, 2008).
thought about leaving and whether or
not the employee experienced a
triggering event.

48. Conclusion
The Federal Human Capital
Survey is a rich data source for
the federal community and for Investigating dissatisfaction is an
organizations who seek important construct in our efforts to
comparisons between the private understand employee perceptions,
and public sector. affective mood and reasons for
disillusion (ME, 2012).
 It has been a rewarding
experience to conduct this
investigation and add to the
conversation about employee
dissatisfaction.

49. References
Bedeian, A.G., Ferris, G. R., & Kacmar, K. M. (1992). Age, tenure and job satisfaction: A tale of two perspectives. Journal of
Vocational Behavior, 40, 33-48. Retrieved from
http://www.bus.lsu.edu/bedeian/articles/AgeTenureAndJobSatisfactionATale-1992.pdf
Berry, J. (2010). A message from John Berry. Retrieved from http://www.fedview.opm.gov/2010/
Bryman, A. (2001). Social research methods. (2nd ed.). Oxford, UK: Oxford Press
Cetin, M. O. (2006). The relationship between job satisfaction, occupational and organizational commitment of academics.
Journal of American Academy of Business, Cambridge, 8(1), 78-88.
Creswell, J.W., & Clark, V.P. (2007). Designing and conducting mixed methods research. Thousand Oaks, CA: Sage
Publications

50. References
DeConinck, J., & Johnson, J. (2009). The effects of perceived supervisor support, perceived organizational support, and
organizational justice on turnover among salespeople. Journal of Personal Selling & Sales Management, 29(14),
333-350. doi:10.2753/PSS0885-3134290403
Detamore, J. A. (2008). An analysis of the relationships between job satisfaction, leadership, and intent to leave within an
engineering consulting firm. Dissertation Abstracts International, 68 (11), 225A. (UMI No. 3289494)
Dychtwald, K., Erickson, T., & Morrison, R. (2006). Workforce crisis: How to beat the coming shortage of skills and talent.
Boston, MA: Harvard Business School Press.
Gelman, A., & Hill, J. (2007). Data analysis using regression and multi-level hierarchical models. New York, NY: Cambridge
University Press.
Judge, T.A., Thoresen, C.J., Bono, J.E., & Patton, G.K. (2001). The job satisfaction–job performance relationship: A qualitative
and quantitative review. Psychological Bulletin, 127(3), 376-407. doi:10.1037/0033-2909.127.3.376

51. References
Kacmar, K. M.& Ferris, G.R. (1989).Theoretical and methodological considerations in the age-job satisfaction relationship. Journal of Applied
Psychology, 74(2), 201- 207. doi: 10.1037/0021-9010.74.2.201
Kalleberg, A. (1977). Work value and job rewards: A theory of job satisfaction. American Sociological Review, 42(2), 124-143. Retrieved
from
http://iscrat.org/soc-pol/wam-net/Launch-mini-conference/WAMSEM6/KALLEBERG%20Work%20values%20and%20job%20rewards.pdf
Murphey, M.G. (1994). Philosophical foundations of historical knowledge. New York, NY: SUNY Press
Rieger, T. (2011). Beware of parochial managers. Gallup Management Journal Online. Retrieved from
http://gmj.gallup.com/content/147653/Beware-Parochial-Managers.aspx
Seashore, S.E., & Taber, T.D. (1975). Job satisfaction indicators and their correlates. American Behavioral Scientist, 18(3), pp.
333-386. Retrieved from http://moodle.nmsu.edu/ocs/index.php/SWAM2010/Dallas/paper/viewFile/166/55

52. Questions and Answers
THANK YOU, ALL
FOR YOUR PARTICIPATION AND CONSIDERATION OF MY
DISSERTATION AND DEFENSE.